qA      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                                                                                        ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@!(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None05[WThe sort order specified in a listing condition. Possible values include the following:asc9 - Present the information in ascending order (from A-Z).dsc: - Present the information in descending order (from Z-A).9A list of the variables to use in searching or filtering . CreatedAt - Sets the search criteria to  creation date.A - Sets the search criteria to  status.Name/ - Sets the search criteria to the contents of  ____ Name.IAMUserK - Sets the search criteria to the user account that invoked an evaluation. MLModelId# - Sets the search criteria to the  Predictor that was evaluated. DataSourceId# - Sets the search criteria to the  used in evaluation.DataUri - Sets the search criteria to the data file(s) used in evaluation. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.%1Object status with the following possible values:PENDING INPROGRESSFAILED COMPLETEDDELETED+Contains the key values of  DetailsMap: - - Indicates the type of the . >1 - Indicates the algorithm that was used for the ..9A list of the variables to use in searching or filtering . CreatedAt - Sets the search criteria to  creation date.A - Sets the search criteria to  status.Name/ - Sets the search criteria to the contents of  ____ Name.DataUriH - Sets the search criteria to the URI of data files used to create the i. The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.IAMUserA - Sets the search criteria to the user account that invoked the  creation.Note:The variable names should match the variable names in the .59A list of the variables to use in searching or filtering . CreatedAt - Sets the search criteria to  creation date.A - Sets the search criteria to  status.Name/ - Sets the search criteria to the contents of  ____ Name.IAMUserA - Sets the search criteria to the user account that invoked the  creation. MLModelId# - Sets the search criteria to the  used in the . DataSourceId# - Sets the search criteria to the  used in the .DataURI< - Sets the search criteria to the data file(s) used in the i. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.>The function used to train an @. Training choices supported by Amazon ML include the following:? - Stochastic Gradient Descent. RandomForest# - Random forest of decision trees.  !"#$%&'()*+,-./0123456789:;<=>?BCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~@  !"#$%&'()*+,-.3/012456789:;<=>?e   !"#$%&'()*+,-./0123456789:;<=>?BCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~ (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None!"05@JA custom key-value pair associated with an ML object, such as an ML model.See:  smart constructor.A&Describes the data specification of a O.See:  smart constructor.BDescribes the O% details specific to Amazon Redshift.See:  smart constructor.C^Describes the database credentials for connecting to a database on an Amazon Redshift cluster.See:  smart constructor.DRDescribes the database details required to connect to an Amazon Redshift database.See:  smart constructor.E7Describes the data specification of an Amazon Redshift O.See:  smart constructor.F4Describes the real-time endpoint information for an M.See:  smart constructor.G7The datasource details that are specific to Amazon RDS.See:  smart constructor.HHThe database credentials to connect to a database on an RDS DB instance.See:  smart constructor.I/The database details of an Amazon RDS database.See:  smart constructor.JMThe data specification of an Amazon Relational Database Service (Amazon RDS) O.See:  smart constructor.KThe output from a Predict operation:Details - Contains the following attributes: 'DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | MULTICLASS' 'DetailsAttributes.ALGORITHM - SGD'PredictedLabel - Present for either a BINARY or  MULTICLASS M request.PredictedScoresE - Contains the raw classification score corresponding to each label.PredictedValue - Present for a  REGRESSION M request.See:  smart constructor.LMeasurements of how well the Me performed on known observations. One of the following metrics is returned, based on the type of the M:BinaryAUC: The binary MF uses the Area Under the Curve (AUC) technique to measure performance.RegressionRMSE: The regression M uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.$MulticlassAvgFScore: The multiclass M4 uses the F1 score technique to measure performance.?For more information about performance metrics, please see the  5http://docs.aws.amazon.com/machine-learning/latest/dg'Amazon Machine Learning Developer Guide.See:  smart constructor.MRepresents the output of a  GetMLModel operation.LThe content consists of the detailed metadata and the current status of the M.See:  smart constructor.NRepresents the output of  GetEvaluation operation.fThe content consists of the detailed metadata and data file information and the current status of the N.See: u smart constructor.ORepresents the output of the  GetDataSource operation.fThe content consists of the detailed metadata and data file information and the current status of the O.See: b smart constructor.PRepresents the output of a GetBatchPrediction operation.qThe content consists of the detailed metadata, the status, and the data file information of a 'Batch Prediction'.See: Q smart constructor.QCreates a value of P4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:RSTUVWXYZ[\]^_`aRThe status of the P4. This element can have one of the following values:PENDINGo - Amazon Machine Learning (Amazon ML) submitted a request to generate predictions for a batch of observations. INPROGRESS - The process is underway.FAILEDY - The request to perform a batch prediction did not run to completion. It is not usable. COMPLETED7 - The batch prediction process completed successfully.DELETED - The P( is marked as deleted. It is not usable.S(The time of the most recent edit to the P&. The time is expressed in epoch time.TThe time that the P2 was created. The time is expressed in epoch time.UUndocumented member.VXThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).WThe ID of the M$ that generated predictions for the P request.XThe ID of the O5 that points to the group of observations to predict.YUndocumented member.ZUndocumented member.[The ID assigned to the PA at creation. This value should be identical to the value of the BatchPredictionID in the request.\Undocumented member.]Undocumented member.^&The AWS user account that invoked the Pq. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account._+A user-supplied name or description of the P.`WA description of the most recent details about processing the batch prediction request.aThe location of an Amazon S3 bucket or directory to receive the operation results. The following substrings are not allowed in the 's3 key' portion of the  outputURI! field: ':', '//', '/./', '/../'.bCreates a value of O4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:cdefghijklmnopqrstcThe current status of the O4. This element can have one of the following values:NPENDING - Amazon Machine Learning (Amazon ML) submitted a request to create a O..INPROGRESS - The creation process is underway.!FAILED - The request to create a O- did not run to completion. It is not usable.8COMPLETED - The creation process completed successfully.DELETED - The O( is marked as deleted. It is not usable.d+The number of data files referenced by the O.e(The time of the most recent edit to the P&. The time is expressed in epoch time.fThe time that the O2 was created. The time is expressed in epoch time.gUndocumented member.hThe ID that is assigned to the O during creation.iUndocumented member.jFThe total number of observations contained in the data files that the O references.kUndocumented member.lUndocumented member.m$The AWS user account from which the O} was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.n+A user-supplied name or description of the O.oaThe location and name of the data in Amazon Simple Storage Service (Amazon S3) that is used by a O.pThe parameter is true> if statistics need to be generated from the observation data.q<A description of the most recent details about creating the O.rUndocumented member.sYA JSON string that represents the splitting and rearrangement requirement used when this O was created.tUndocumented member.uCreates a value of N4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:vwxyz{|}~vPThe status of the evaluation. This element can have one of the following values:PENDINGJ - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an M. INPROGRESS - The evaluation is underway.FAILED - The request to evaluate an M- did not run to completion. It is not usable. COMPLETED1 - The evaluation process completed successfully.DELETED - The N( is marked as deleted. It is not usable.wMeasurements of how well the M1 performed, using observations referenced by the OE. One of the following metrics is returned, based on the type of the M:BinaryAUC: A binary MF uses the Area Under the Curve (AUC) technique to measure performance.RegressionRMSE: A regression M uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable."MulticlassAvgFScore: A multiclass M4 uses the F1 score technique to measure performance.?For more information about performance metrics, please see the  5http://docs.aws.amazon.com/machine-learning/latest/dg'Amazon Machine Learning Developer Guide.x(The time of the most recent edit to the N&. The time is expressed in epoch time.yThe time that the N2 was created. The time is expressed in epoch time.zUndocumented member.{mThe location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.|The ID of the M% that is the focus of the evaluation.}Undocumented member.~Undocumented member.The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.+A user-supplied name or description of the N.The ID that is assigned to the N at creation.>A description of the most recent details about evaluating the M.The ID of the O that is used to evaluate the M.Creates a value of M4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The current status of an M4. This element can have one of the following values:PENDINGH - Amazon Machine Learning (Amazon ML) submitted a request to create an M. INPROGRESS$ - The creation process is underway.FAILED - The request to create an M2 didn't run to completion. The model isn't usable. COMPLETED/ - The creation process completed successfully.DELETED - The M' is marked as deleted. It isn't usable.(The time of the most recent edit to the M&. The time is expressed in epoch time.)A list of the training parameters in the M6. The list is implemented as a map of key-value pairs.8The following is the current set of training parameters:'sgd.maxMLModelSizeInBytes'z - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance.)The value is an integer that ranges from '100000' to  '2147483648'. The default value is  '33554432'.'sgd.maxPasses'Y - The number of times that the training process traverses the observations to build the M+. The value is an integer that ranges from '1' to '10000'. The default value is '10'.'sgd.shuffleType' - Whether Amazon ML shuffles the training data. Shuffling the data improves a model's ability to find the optimal solution for a variety of data types. The valid values are auto and none. The default value is none.'sgd.l1RegularizationAmount' - The coefficient regularization L1 norm, which controls overfitting the data by penalizing large coefficients. This parameter tends to drive coefficients to zero, resulting in sparse feature set. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L1 normalization. This parameter can't be used when L2, is specified. Use this parameter sparingly.'sgd.l2RegularizationAmount' - The coefficient regularization L2 norm, which controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L2 normalization. This parameter can't be used when L1, is specified. Use this parameter sparingly.(The time of the most recent edit to the ScoreThreshold&. The time is expressed in epoch time.The time that the M2 was created. The time is expressed in epoch time.Undocumented member.XThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).The ID assigned to the M at creation.Undocumented member.Undocumented member.Undocumented member.Undocumented member. The algorithm used to train the M'. The following algorithm is supported:?- -- Stochastic gradient descent. The goal of ?2 is to minimize the gradient of the loss function.$The AWS user account from which the M} was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.+A user-supplied name or description of the M.The current endpoint of the M.The ID of the training O. The  CreateMLModel operation uses the TrainingDataSourceId.=A description of the most recent details about accessing the M.Identifies the M1 category. The following are the available types: REGRESSIONT - Produces a numeric result. For example, "What price should a house be listed at?"BINARY[ - Produces one of two possible results. For example, "Is this a child-friendly web site?". MULTICLASS[ - Produces one of several possible results. For example, "Is this a HIGH-, LOW-, or MEDIUM risk trade?".Creates a value of L4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Undocumented member.Creates a value of K4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The prediction value for  REGRESSION M."The prediction label for either a BINARY or  MULTICLASS M.Undocumented member.Undocumented member.Creates a value of J4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: The Amazon S3 location of the  DataSchema.;A JSON string that represents the schema for an Amazon RDS O. The  DataSchemaU defines the structure of the observation data in the data file(s) referenced in the O.A  DataSchema" is not required if you specify a  DataSchemaUri Define your  DataSchema! as a series of key-value pairs.  attributes and excludedVariableNames[ have an array of key-value pairs for their value. Use the following format to define your  DataSchema.{ "version": "1.0",""recordAnnotationFieldName": "F1","recordWeightFieldName": "F2","targetFieldName": "F3","dataFormat": "CSV","dataFileContainsHeader": true,"attributes": [{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],#"excludedVariableNames": [ "F6" ] }\A JSON string that represents the splitting and rearrangement processing to be applied to a O . If the DataRearrangementH parameter is not provided, all of the input data is used to create the  Datasource.TThere are multiple parameters that control what data is used to create a datasource: percentBeginUse  percentBegini to indicate the beginning of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. percentEndUse  percentEndc to indicate the end of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. complementThe  complementT parameter instructs Amazon ML to use the data that is not included in the range of  percentBegin to  percentEnd to create a datasource. The  complement parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for  percentBegin and  percentEnd, along with the  complement parameter.For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data.NDatasource for evaluation: '{"splitting":{"percentBegin":0, "percentEnd":25}}'aDatasource for training: '{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}'strategyBTo change how Amazon ML splits the data for a datasource, use the strategy parameter.The default value for the strategy parameter is  sequentialC, meaning that Amazon ML takes all of the data records between the  percentBegin and  percentEndW parameters for the datasource, in the order that the records appear in the input data.The following two DataRearrangementP lines are examples of sequentially ordered training and evaluation datasources:iDatasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}'|Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}'wTo randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the strategy parameter to randomW and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between  percentBegin and  percentEnd. Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records.The following two DataRearrangementT lines are examples of non-sequentially ordered training and evaluation datasources:Datasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}'Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}'Describes the  DatabaseName and InstanceIdentifier of an Amazon RDS database.@The query that is used to retrieve the observation data for the O.jThe AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon RDS database.]The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery is stored in this location.The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute Cloud (Amazon EC2) instance to carry out the copy operation from Amazon RDS to an Amazon S3 task. For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.The subnet ID to be used to access a VPC-based RDS DB instance. This attribute is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon S3.The security group IDs to be used to access a VPC-based RDS DB instance. Ensure that there are appropriate ingress rules set up to allow access to the RDS DB instance. This attribute is used by Data Pipeline to carry out the copy operation from Amazon RDS to an Amazon S3 task.Creates a value of I4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID of an RDS DB instance.Undocumented member.Creates a value of H4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Undocumented member.Undocumented member.Creates a value of G4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:&The SQL query that is supplied during  CreateDataSourceFromRDS. Returns only if Verbose is true in GetDataSourceInput.The ID of the Data Pipeline instance that is used to carry to copy data from Amazon RDS to Amazon S3. You can use the ID to find details about the instance in the Data Pipeline console.:The database details required to connect to an Amazon RDS.Undocumented member.The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance to carry out the copy task from Amazon RDS to Amazon S3. For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.Creates a value of F4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:CThe time that the request to create the real-time endpoint for the M3 was received. The time is expressed in epoch time.KThe URI that specifies where to send real-time prediction requests for the M.NoteVThe application must wait until the real-time endpoint is ready before using this URI.5The current status of the real-time endpoint for the M4. This element can have one of the following values:NONE5 - Endpoint does not exist or was previously deleted.READY: - Endpoint is ready to be used for real-time predictions.UPDATING" - Updating/creating the endpoint.;The maximum processing rate for the real-time endpoint for M+, measured in incoming requests per second.Creates a value of E4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:5Describes the schema location for an Amazon Redshift O.@A JSON string that represents the schema for an Amazon Redshift O. The  DataSchemaU defines the structure of the observation data in the data file(s) referenced in the O.A  DataSchema" is not required if you specify a  DataSchemaUri. Define your  DataSchema! as a series of key-value pairs.  attributes and excludedVariableNames[ have an array of key-value pairs for their value. Use the following format to define your  DataSchema.{ "version": "1.0",""recordAnnotationFieldName": "F1","recordWeightFieldName": "F2","targetFieldName": "F3","dataFormat": "CSV","dataFileContainsHeader": true,"attributes": [{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],#"excludedVariableNames": [ "F6" ] }\A JSON string that represents the splitting and rearrangement processing to be applied to a O . If the DataRearrangementH parameter is not provided, all of the input data is used to create the  Datasource.TThere are multiple parameters that control what data is used to create a datasource: percentBeginUse  percentBegini to indicate the beginning of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. percentEndUse  percentEndc to indicate the end of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. complementThe  complementT parameter instructs Amazon ML to use the data that is not included in the range of  percentBegin to  percentEnd to create a datasource. The  complement parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for  percentBegin and  percentEnd, along with the  complement parameter.For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data.NDatasource for evaluation: '{"splitting":{"percentBegin":0, "percentEnd":25}}'aDatasource for training: '{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}'strategyBTo change how Amazon ML splits the data for a datasource, use the strategy parameter.The default value for the strategy parameter is  sequentialC, meaning that Amazon ML takes all of the data records between the  percentBegin and  percentEndW parameters for the datasource, in the order that the records appear in the input data.The following two DataRearrangementP lines are examples of sequentially ordered training and evaluation datasources:iDatasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}'|Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}'wTo randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the strategy parameter to randomW and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between  percentBegin and  percentEnd. Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records.The following two DataRearrangementT lines are examples of non-sequentially ordered training and evaluation datasources:Datasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}'Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}'Describes the  DatabaseName and ClusterIdentifier for an Amazon Redshift O.YDescribes the SQL Query to execute on an Amazon Redshift database for an Amazon Redshift O.uDescribes AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon Redshift database.?Describes an Amazon S3 location to store the result set of the SelectSqlQuery query.Creates a value of D4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Undocumented member.Undocumented member.Creates a value of C4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Undocumented member.Undocumented member.Creates a value of B4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:'The SQL query that is specified during  CreateDataSourceFromRedshift. Returns only if Verbose is true in GetDataSourceInput.Undocumented member.Undocumented member.Creates a value of A4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired::A JSON string that represents the schema for an Amazon S3 O. The  DataSchemaU defines the structure of the observation data in the data file(s) referenced in the O.You must provide either the  DataSchema or the DataSchemaLocationS3. Define your  DataSchema! as a series of key-value pairs.  attributes and excludedVariableNames[ have an array of key-value pairs for their value. Use the following format to define your  DataSchema.{ "version": "1.0",""recordAnnotationFieldName": "F1","recordWeightFieldName": "F2","targetFieldName": "F3","dataFormat": "CSV","dataFileContainsHeader": true,"attributes": [{ "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ],#"excludedVariableNames": [ "F6" ] }HDescribes the schema location in Amazon S3. You must provide either the  DataSchema or the DataSchemaLocationS3.\A JSON string that represents the splitting and rearrangement processing to be applied to a O . If the DataRearrangementH parameter is not provided, all of the input data is used to create the  Datasource.TThere are multiple parameters that control what data is used to create a datasource: percentBeginUse  percentBegini to indicate the beginning of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. percentEndUse  percentEndc to indicate the end of the range of the data used to create the Datasource. If you do not include  percentBegin and  percentEndB, Amazon ML includes all of the data when creating the datasource. complementThe  complementT parameter instructs Amazon ML to use the data that is not included in the range of  percentBegin to  percentEnd to create a datasource. The  complement parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for  percentBegin and  percentEnd, along with the  complement parameter.For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data.NDatasource for evaluation: '{"splitting":{"percentBegin":0, "percentEnd":25}}'aDatasource for training: '{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}'strategyBTo change how Amazon ML splits the data for a datasource, use the strategy parameter.The default value for the strategy parameter is  sequentialC, meaning that Amazon ML takes all of the data records between the  percentBegin and  percentEndW parameters for the datasource, in the order that the records appear in the input data.The following two DataRearrangementP lines are examples of sequentially ordered training and evaluation datasources:iDatasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}'|Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}'wTo randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the strategy parameter to randomW and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between  percentBegin and  percentEnd. Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records.The following two DataRearrangementT lines are examples of non-sequentially ordered training and evaluation datasources:Datasource for evaluation: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}'Datasource for training: '{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}'+The location of the data file(s) used by a Oz. The URI specifies a data file or an Amazon Simple Storage Service (Amazon S3) directory or bucket containing data files.Creates a value of @4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:An optional string, typically used to describe or define the tag. Valid characters include Unicode letters, digits, white space, _, ., /, =, +, -, %, and '.{A unique identifier for the tag. Valid characters include Unicode letters, digits, white space, _, ., /, =, +, -, %, and '.S@ABCDEFGHIJKLMNO     P !QRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVW@ABCDEFGHIJKLMNO     P !QRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~@ABCDEFGHIJ KLMNO     P !QRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVW(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None  API version  '2014-12-12'2 of the Amazon Machine Learning SDK configuration.&Prism for InvalidTagException' errors.AAn error on the server occurred when trying to process a request.PAn error on the client occurred. Typically, the cause is an invalid input value.A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.,Prism for TagLimitExceededException' errors.GThe exception is thrown when a predict request is made to an unmounted M.'A specified resource cannot be located.pThe subscriber exceeded the maximum number of operations. This exception can occur when listing objects such as O.   !"#$%&'()*+,-.3/012456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~>?56789:;<=./01234+,-%&'()* !"#$  PQRSTUVWXYZ[\]^_`aObcdefghijklmnopqrstNuvwxyz{|}~MLKJIHGFEDCBA@ (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR$Represents the query results from a  DescribeDataSources1 operation. The content is essentially a list of O.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: The equal to operator. The O results will have FilterVariable4 values that exactly match the value specified with X.+The greater than or equal to operator. The O results will have FilterVariableC values that are greater than or equal to the value specified with GE.?A string that is found at the beginning of a variable, such as Name or Id.For example, a O could have the Name '2014-09-09-HolidayGiftMailer'. To search for this O , select Name for the FilterVariable* and any of the following strings for the Prefix:2014-09 2014-09-092014-09-09-HolidayThe greater than operator. The O results will have FilterVariable7 values that are greater than the value specified with Y.The not equal to operator. The O results will have FilterVariable. values not equal to the value specified with NE.,The ID of the page in the paginated results.LA two-value parameter that determines the sequence of the resulting list of O.asc3 - Arranges the list in ascending order (A-Z, 0-9).dsc4 - Arranges the list in descending order (Z-A, 9-0).Results are sorted by FilterVariable.The maximum number of O to include in the result.The less than operator. The O results will have FilterVariable4 values that are less than the value specified with Z.7Use one of the following variables to filter a list of O: CreatedAt - Sets the search criteria to O creation dates.A - Sets the search criteria to O statuses.Name/ - Sets the search criteria to the contents of O ____ Name.DataUriH - Sets the search criteria to the URI of data files used to create the Oi. The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.IAMUserA - Sets the search criteria to the user account that invoked the O creation.(The less than or equal to operator. The O results will have FilterVariable@ values that are less than or equal to the value specified with LE.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: A list of O that meet the search criteria.^An ID of the next page in the paginated results that indicates at least one more page follows.The response status code.+[\]^_`abcdefghij[\]^ _`abcdefghij(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a 1 operation. The content is essentially a list of M.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:      The equal to operator. The M results will have FilterVariable4 values that exactly match the value specified with X. +The greater than or equal to operator. The M results will have FilterVariableC values that are greater than or equal to the value specified with GE. ?A string that is found at the beginning of a variable, such as Name or Id.For example, an M could have the Name '2014-09-09-HolidayGiftMailer'. To search for this M , select Name for the FilterVariable* and any of the following strings for the Prefix:2014-09 2014-09-092014-09-09-Holiday The greater than operator. The M results will have FilterVariable7 values that are greater than the value specified with Y. The not equal to operator. The M results will have FilterVariable. values not equal to the value specified with NE. ,The ID of the page in the paginated results.LA two-value parameter that determines the sequence of the resulting list of M.asc3 - Arranges the list in ascending order (A-Z, 0-9).dsc4 - Arranges the list in descending order (Z-A, 9-0).Results are sorted by FilterVariable._The number of pages of information to include in the result. The range of acceptable values is '1' through '100'. The default value is '100'.The less than operator. The M results will have FilterVariable4 values that are less than the value specified with Z.7Use one of the following variables to filter a list of M:  CreatedAt - Sets the search criteria to M creation date.A - Sets the search criteria to M status.Name/ - Sets the search criteria to the contents of M ____ Name.IAMUserA - Sets the search criteria to the user account that invoked the M creation.TrainingDataSourceId# - Sets the search criteria to the O used to train one or more M.# - Sets the search criteria to the M real-time endpoint status.  - Sets the search criteria to M* type: binary, regression, or multi-class.>6 - Sets the search criteria to the algorithm that the M uses.TrainingDataURIC - Sets the search criteria to the data file(s) used in training a Mi. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.(The less than or equal to operator. The M results will have FilterVariable@ values that are less than or equal to the value specified with LE.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: A list of M that meet the search criteria._The ID of the next page in the paginated results that indicates at least one more page follows.The response status code.+klmnopqrstuvwxyz               klmn opqrstuvwxyz     (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR *)Amazon ML returns the following elements.See: 0 smart constructor.+See: , smart constructor.,Creates a value of +4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:-./-The key-value pairs to use to create tags. If you specify a key without specifying a value, Amazon ML creates a tag with the specified key and a value of null..-The ID of the ML object to tag. For example, exampleModelId./!The type of the ML object to tag.0Creates a value of *4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:1231(The ID of the ML object that was tagged.2*The type of the ML object that was tagged.3The response status code.*{|}~+,./-./03123456789:; *+,-./0123 ,+-./0*123*{|}~+,-./0123456789:;(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRFRepresents the output of an G operation.The result contains the  MLModelId& and the endpoint information for the M.1The endpoint information includes the URI of the MM; that is, the location to send online prediction requests for the specified M.See: J smart constructor.GSee: H smart constructor.HCreates a value of G4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:IIThe ID assigned to the M during creation.JCreates a value of F4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:KLMK The endpoint information of the ML0A user-supplied ID that uniquely identifies the M5. This value should be identical to the value of the  MLModelId in the request.MThe response status code.FGHIIJMKLMNOPQRSTUFGHIJKLMHGIJFKLMFGHIJKLMNOPQRSTU(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR`$Represents the query results from a a1 operation. The content is essentially a list of N.See: n smart constructor.aSee: b smart constructor.bCreates a value of a4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: cdefghijklmcThe equal to operator. The N results will have FilterVariable4 values that exactly match the value specified with X.d+The greater than or equal to operator. The N results will have FilterVariableC values that are greater than or equal to the value specified with GE.e?A string that is found at the beginning of a variable, such as Name or Id.For example, an N could have the Name '2014-09-09-HolidayGiftMailer'. To search for this N , select Name for the FilterVariable* and any of the following strings for the Prefix:2014-09 2014-09-092014-09-09-HolidayfThe greater than operator. The N results will have FilterVariable7 values that are greater than the value specified with Y.gThe not equal to operator. The N results will have FilterVariable. values not equal to the value specified with NE.h,The ID of the page in the paginated results.iLA two-value parameter that determines the sequence of the resulting list of N.asc3 - Arranges the list in ascending order (A-Z, 0-9).dsc4 - Arranges the list in descending order (Z-A, 9-0).Results are sorted by FilterVariable.jThe maximum number of N to include in the result.kThe less than operator. The N results will have FilterVariable4 values that are less than the value specified with Z.l6Use one of the following variable to filter a list of N objects: CreatedAt# - Sets the search criteria to the N creation date.A# - Sets the search criteria to the N status.Name/ - Sets the search criteria to the contents of N ____ Name.IAMUser@ - Sets the search criteria to the user account that invoked an N. MLModelId# - Sets the search criteria to the M that was evaluated. DataSourceId# - Sets the search criteria to the O used in N.DataUri8 - Sets the search criteria to the data file(s) used in Nj. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.m(The less than or equal to operator. The N results will have FilterVariable@ values that are less than or equal to the value specified with LE.nCreates a value of `4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:opqo A list of N that meet the search criteria.p_The ID of the next page in the paginated results that indicates at least one more page follows.qThe response status code.+`abcdefghijklmnqopqrstuvwxyz`abcdefghijklmnopqbacdefghijklmn`opq`a bcdefghijklmnopqrstuvwxyz(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a  operation and describes an N.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID of the N% to retrieve. The evaluation of each MP is recorded and cataloged. The ID provides the means to access the information.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:PThe status of the evaluation. This element can have one of the following values:PENDINGJ - Amazon Machine Language (Amazon ML) submitted a request to evaluate an M. INPROGRESS - The evaluation is underway.FAILED - The request to evaluate an M- did not run to completion. It is not usable. COMPLETED1 - The evaluation process completed successfully.DELETED - The N( is marked as deleted. It is not usable.Measurements of how well the M0 performed using observations referenced by the OC. One of the following metric is returned based on the type of the M:BinaryAUC: A binary MF uses the Area Under the Curve (AUC) technique to measure performance.RegressionRMSE: A regression M uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable."MulticlassAvgFScore: A multiclass M4 uses the F1 score technique to measure performance.?For more information about performance metrics, please see the  5http://docs.aws.amazon.com/machine-learning/latest/dg'Amazon Machine Learning Developer Guide.(The time of the most recent edit to the N&. The time is expressed in epoch time.The time that the N2 was created. The time is expressed in epoch time.[The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the N2, normalized and scaled on computation resources.  ComputeTime is only available if the N is in the  COMPLETED state.XThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).The ID of the M& that was the focus of the evaluation.7The epoch time when Amazon Machine Learning marked the N as  INPROGRESS.  StartedAt isn't available if the N is in the PENDING state.7The epoch time when Amazon Machine Learning marked the N as  COMPLETED or FAILED.  FinishedAt is only available when the N is in the  COMPLETED or FAILED state.The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.+A user-supplied name or description of the N.-A link to the file that contains logs of the CreateEvaluation operation.'The evaluation ID which is same as the  EvaluationId in the request.>A description of the most recent details about evaluating the M.The O used for this evaluation.The response status code.0(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.The I operation is asynchronous. You can poll for status updates by using the '>GetBatchPrediction' operation and checking the A parameter of the result.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:+A user-supplied name or description of the P. BatchPredictionName& can only use the UTF-8 character set.0A user-supplied ID that uniquely identifies the P.The ID of the M> that will generate predictions for the group of observations.The ID of the O5 that points to the group of observations to predict.The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory to store the batch prediction results. The following substrings are not allowed in the 's3 key' portion of the  outputURI! field: ':', '//', '/./', '/../'.Amazon ML needs permissions to store and retrieve the logs on your behalf. For information about how to set permissions, see the  5http://docs.aws.amazon.com/machine-learning/latest/dg'Amazon Machine Learning Developer Guide.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the P.. This value is identical to the value of the BatchPredictionId in the request.The response status code.   (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of an  operation.The result contains the  MLModelId& and the endpoint information for the M.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID assigned to the M during creation.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: The endpoint information of the M0A user-supplied ID that uniquely identifies the M5. This value should be identical to the value of the  MLModelId in the request.The response status code. (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:A unique identifier of the M.Undocumented member.Undocumented member.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Undocumented member.The response status code.   (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.I operation is asynchronous. You can poll for status updates by using the GetEvcaluation operation and checking the A parameter.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:+A user-supplied name or description of the N.0A user-supplied ID that uniquely identifies the N.The ID of the M to evaluate. The schema used in creating the M must match the schema of the O used in the N.The ID of the O' for the evaluation. The schema of the O* must match the schema used to create the M.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:2The user-supplied ID that uniquely identifies the N5. This value should be identical to the value of the  EvaluationId in the request.The response status code.             (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.The C> operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the A parameter. You can inspect the Message when A shows up as FAILEDH. You can also check the progress of the copy operation by going to the  DataPipelineT console and looking up the pipeline using the 'pipelineId ' from the describe call.See: " smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: !+A user-supplied name or description of the O.The compute statistics for a OI. The statistics are generated from the observation data referenced by a O2. Amazon ML uses the statistics internally during M) training. This parameter must be set to true if the ' needs to be used for M training.0A user-supplied ID that uniquely identifies the OB. Typically, an Amazon Resource Number (ARN) becomes the ID for a O. (The data specification of an Amazon RDS O: DatabaseInformation - DatabaseName' - The name of the Amazon RDS database.'InstanceIdentifier ' - A unique identifier for the Amazon RDS database instance. - DatabaseCredentials - AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon RDS database.ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by an EC2 instance to carry out the copy task from Amazon RDS to Amazon Simple Storage Service (Amazon S3). For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see  Ohttp://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.htmlRole templates for data pipelines.SecurityInfo - The security information to use to access an RDS DB instance. You need to set up appropriate ingress rules for the security entity IDs provided to allow access to the Amazon RDS instance. Specify a [SubnetId, SecurityGroupIds'] pair for a VPC-based RDS DB instance.OSelectSqlQuery - A query that is used to retrieve the observation data for the  Datasource.qS3StagingLocation - The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using SelectSqlQuery is stored in this location..DataSchemaUri - The Amazon S3 location of the  DataSchema.LDataSchema - A JSON string representing the schema. This is not required if  DataSchemaUri is specified.gDataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the  Datasource.ESample - ' "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"'!The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user's account and copy data using the SelectSqlQuery$ query from Amazon RDS to Amazon S3."Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:#$#oA user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the  DataSourceID in the request.$The response status code. ! !"$#$%&'()*+,  !"#$  !"#$ !"#$%&'()*+, (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR7Represents the output of a 81 operation. The content is essentially a list of Ps.See: E smart constructor.8See: 9 smart constructor.9Creates a value of 84 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: :;<=>?@ABCD:The equal to operator. The P results will have FilterVariable4 values that exactly match the value specified with X.;+The greater than or equal to operator. The P results will have FilterVariableC values that are greater than or equal to the value specified with GE.<?A string that is found at the beginning of a variable, such as Name or Id.;For example, a 'Batch Prediction' operation could have the Name '2014-09-09-HolidayGiftMailer'. To search for this P , select Name for the FilterVariable* and any of the following strings for the Prefix:2014-09 2014-09-092014-09-09-Holiday=The greater than operator. The P results will have FilterVariable7 values that are greater than the value specified with Y.>The not equal to operator. The P results will have FilterVariable. values not equal to the value specified with NE.?+An ID of the page in the paginated results.@LA two-value parameter that determines the sequence of the resulting list of Ms.asc3 - Arranges the list in ascending order (A-Z, 0-9).dsc4 - Arranges the list in descending order (Z-A, 9-0).Results are sorted by FilterVariable.A_The number of pages of information to include in the result. The range of acceptable values is '1' through '100'. The default value is '100'.BThe less than operator. The P results will have FilterVariable4 values that are less than the value specified with Z.C7Use one of the following variables to filter a list of P: CreatedAt# - Sets the search criteria to the P creation date.A# - Sets the search criteria to the P status.Name3 - Sets the search criteria to the contents of the P ____ Name.IAMUserA - Sets the search criteria to the user account that invoked the P creation. MLModelId# - Sets the search criteria to the M used in the P. DataSourceId# - Sets the search criteria to the O used in the P.DataURI< - Sets the search criteria to the data file(s) used in the Pj. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.D(The less than or equal to operator. The P results will have FilterVariable@ values that are less than or equal to the value specified with LE.ECreates a value of 74 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:FGHF A list of P' objects that meet the search criteria.G_The ID of the next page in the paginated results that indicates at least one more page follows.HThe response status code.+789:;<=>?@ABCDEHFGHIJKLMNOPQ789:;<=>?@ABCDEFGH98:;<=>?@ABCDE7FGH78 9:;<=>?@ABCDEFGHIJKLMNOPQ(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)NoneDR\Polls !"d every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.]Polls !#d every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.^Polls !$d every 30 seconds until a successful state is reached. An error is returned after 60 failed checks._Polls !%d every 30 seconds until a successful state is reached. An error is returned after 60 failed checks.\]^_\]^_\]^_\]^_(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR`Represents the output of a a operation and describes a P.See: d smart constructor.aSee: b smart constructor.bCreates a value of a4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:ccAn ID assigned to the P at creation.dCreates a value of `4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:efghijklmnopqrstuveThe status of the P+, which can be one of the following values:PENDINGY - Amazon Machine Learning (Amazon ML) submitted a request to generate batch predictions. INPROGRESS) - The batch predictions are in progress.FAILEDY - The request to perform a batch prediction did not run to completion. It is not usable. COMPLETED7 - The batch prediction process completed successfully.DELETED - The P( is marked as deleted. It is not usable.f$The time of the most recent edit to P&. The time is expressed in epoch time.gThe time when the P2 was created. The time is expressed in epoch time.h[The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the P2, normalized and scaled on computation resources.  ComputeTime is only available if the P is in the  COMPLETED state.iXThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).jThe ID of the M$ that generated predictions for the P request.kThe ID of the O that was used to create the P.lRThe number of total records that Amazon Machine Learning saw while processing the P.m7The epoch time when Amazon Machine Learning marked the P as  INPROGRESS.  StartedAt isn't available if the P is in the PENDING state.nAn ID assigned to the PA at creation. This value should be identical to the value of the BatchPredictionID in the request.o7The epoch time when Amazon Machine Learning marked the P as  COMPLETED or FAILED.  FinishedAt is only available when the P is in the  COMPLETED or FAILED state.pTThe number of invalid records that Amazon Machine Learning saw while processing the P.q&The AWS user account that invoked the Pq. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.r+A user-supplied name or description of the P.s-A link to the file that contains logs of the CreateBatchPrediction operation.tWA description of the most recent details about processing the batch prediction request.uRThe location of an Amazon S3 bucket or directory to receive the operation results.vThe response status code.4`abccdvefghijklmnopqrstuvwxyz{|}~`abcdefghijklmnopqrstuvbacd`efghijklmnopqrstuv`abcdefghijklmnopqrstuvwxyz{|}~(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of an  operation.-You can see the updated content by using the  GetMLModel operation.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:+A user-supplied name or description of the M.The ScoreThreshold used in binary classification MQ that marks the boundary between a positive prediction and a negative prediction.+Output values greater than or equal to the ScoreThreshold$ receive a positive result from the M , such as true. Output values less than the ScoreThreshold& receive a negative response from the M , such as false.The ID assigned to the M during creation.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID assigned to the ME during creation. This value should be identical to the value of the  MLModelID in the request.The response status code.  (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a  operation.You can use the  GetMLModel& operation and check the value of the A parameter to see whether an M is marked as DELETED.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the M.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the M5. This value should be identical to the value of the  MLModelID in the request.The response status code.(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a _ operation. The output indicates that Amazon Machine Learning (Amazon ML) received the request.You can use the  GetEvaluation& operation and check the value of the A parameter to see whether an N is marked as DELETED.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the N to delete.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the N5. This value should be identical to the value of the  EvaluationId in the request.The response status code.(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of an  operation.-You can see the updated content by using the  GetEvaluation operation.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID assigned to the N during creation./A new user-supplied name or description of the N' that will replace the current content.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID assigned to the NE during creation. This value should be identical to the value of the N in the request.The response status code.          (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a  operation and describes a O.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:Specifies whether the  operation should return DataSourceSchema. If true, DataSourceSchema is returned. If false, DataSourceSchema is not returned.The ID assigned to the O at creation.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:  The current status of the O4. This element can have one of the following values:PENDING- - Amazon ML submitted a request to create a O. INPROGRESS$ - The creation process is underway.FAILED - The request to create a O- did not run to completion. It is not usable. COMPLETED/ - The creation process completed successfully.DELETED - The O( is marked as deleted. It is not usable.+The number of data files referenced by the O.(The time of the most recent edit to the O&. The time is expressed in epoch time.The time that the O2 was created. The time is expressed in epoch time.[The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the O2, normalized and scaled on computation resources.  ComputeTime is only available if the O is in the  COMPLETED state and the ComputeStatistics is set to true.The ID assigned to the OA at creation. This value should be identical to the value of the  DataSourceId in the request.Undocumented member.1The total size of observations in the data files.1The schema used by all of the data files of this O.Note9This parameter is provided as part of the verbose format.7The epoch time when Amazon Machine Learning marked the O as  INPROGRESS.  StartedAt isn't available if the O is in the PENDING state.7The epoch time when Amazon Machine Learning marked the O as  COMPLETED or FAILED.  FinishedAt is only available when the O is in the  COMPLETED or FAILED state.$The AWS user account from which the O} was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.+A user-supplied name or description of the O.&A link to the file containing logs of 'CreateDataSourceFrom*' operations.XThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).The parameter is true> if statistics need to be generated from the observation data.LThe user-supplied description of the most recent details about creating the O.Undocumented member.YA JSON string that represents the splitting and rearrangement requirement used when this O was created. Undocumented member. The response status code.< !"#$%&'          # !"#$%&'     (c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a 6 operation, and provides detailed information about a M.See: " smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired: ! Specifies whether the  operation should return Recipe. If true, Recipe is returned. If false, Recipe is not returned.!The ID assigned to the M at creation."Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:#$%&'()*+,-./012345678#The current status of the M4. This element can have one of the following values:PENDINGI - Amazon Machine Learning (Amazon ML) submitted a request to describe a M. INPROGRESS - The request is processing.FAILEDD - The request did not run to completion. The ML model isn't usable. COMPLETED& - The request completed successfully.DELETED - The M' is marked as deleted. It isn't usable.$(The time of the most recent edit to the M&. The time is expressed in epoch time.%)A list of the training parameters in the M6. The list is implemented as a map of key-value pairs.8The following is the current set of training parameters:'sgd.maxMLModelSizeInBytes'z - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance.)The value is an integer that ranges from '100000' to  '2147483648'. The default value is  '33554432'.'sgd.maxPasses'Y - The number of times that the training process traverses the observations to build the M+. The value is an integer that ranges from '1' to '10000'. The default value is '10'.'sgd.shuffleType' - Whether Amazon ML shuffles the training data. Shuffling data improves a model's ability to find the optimal solution for a variety of data types. The valid values are auto and none. The default value is none3. We strongly recommend that you shuffle your data.'sgd.l1RegularizationAmount' - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L1 normalization. This parameter can't be used when L2, is specified. Use this parameter sparingly.'sgd.l2RegularizationAmount' - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L2 normalization. This parameter can't be used when L1, is specified. Use this parameter sparingly.&(The time of the most recent edit to the ScoreThreshold&. The time is expressed in epoch time.'The time that the M2 was created. The time is expressed in epoch time.([The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the M2, normalized and scaled on computation resources.  ComputeTime is only available if the M is in the  COMPLETED state.)$The recipe to use when training the M. The Recipe provides detailed information about the observation data to use during training, and manipulations to perform on the observation data during training.Note9This parameter is provided as part of the verbose format.*XThe location of the data file or directory in Amazon Simple Storage Service (Amazon S3).+%The MLModel ID, which is same as the  MLModelId in the request.,Undocumented member.-;The schema used by all of the data files referenced by the O.Note9This parameter is provided as part of the verbose format..7The epoch time when Amazon Machine Learning marked the M as  INPROGRESS.  StartedAt isn't available if the M is in the PENDING state./7The scoring threshold is used in binary classification MW models. It marks the boundary between a positive prediction and a negative prediction.iOutput values greater than or equal to the threshold receive a positive result from the MLModel, such as true^. Output values less than the threshold receive a negative response from the MLModel, such as false.07The epoch time when Amazon Machine Learning marked the M as  COMPLETED or FAILED.  FinishedAt is only available when the M is in the  COMPLETED or FAILED state.1$The AWS user account from which the M} was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.2+A user-supplied name or description of the M.3-A link to the file that contains logs of the  CreateMLModel operation.4The current endpoint of the M5The ID of the training O.6=A description of the most recent details about accessing the M.7Identifies the M1 category. The following are the available types:_REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?"]BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?"pMULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?"8The response status code.>()*+,-./0123456789:;<=>?@A! !"8#$%&'()*+,-./0123456789:;<=>?@ !"#$%&'()*+,-./012345678 !"#$%&'()*+,-./012345678$()*+,-./0123456789:;<=>?@A !"#$%&'()*+,-./0123456789:;<=>?@(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRKRepresents the output of an L operation.-You can see the updated content by using the GetBatchPrediction operation.See: P smart constructor.LSee: M smart constructor.MCreates a value of L4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:NONThe ID assigned to the P during creation.O/A new user-supplied name or description of the P.PCreates a value of K4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:QRQThe ID assigned to the PE during creation. This value should be identical to the value of the BatchPredictionId in the request.RThe response status code.KBCDLEFGMNONOPRQRSTUVWXYZKLMNOPQRMLNOPKQRKBCDLEFGMNOPQRSTUVWXYZ(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DReRepresents the output of a f operation.You can use the GetBatchPrediction& operation and check the value of the A parameter to see whether a P is marked as DELETED.See: i smart constructor.fSee: g smart constructor.gCreates a value of f4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:hh0A user-supplied ID that uniquely identifies the P.iCreates a value of e4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:jkj0A user-supplied ID that uniquely identifies the P5. This value should be identical to the value of the BatchPredictionID in the request.kThe response status code.eHIJfKLghhikjklmnopqrsefghijkgfhiejkeHIJfKLghijklmnopqrs(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR ~)Amazon ML returns the following elements.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:One or more tags to delete.-The ID of the tagged ML object. For example, exampleModelId.!The type of the tagged ML object.Creates a value of ~4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:5The ID of the ML object from which tags were deleted.7The type of the ML object from which tags were deleted.The response status code.~MNOPQRST ~ ~~MNOPQRST(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.The I operation is asynchronous. You can poll for status updates by using the  GetMLModel operation and checking the A parameter.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:!The data recipe for creating the Mw. You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default.WThe Amazon Simple Storage Service (Amazon S3) location and file name that contains the M~ recipe. You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default.+A user-supplied name or description of the M.)A list of the training parameters in the M6. The list is implemented as a map of key-value pairs.8The following is the current set of training parameters:'sgd.maxMLModelSizeInBytes'z - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance.)The value is an integer that ranges from '100000' to  '2147483648'. The default value is  '33554432'.'sgd.maxPasses'Y - The number of times that the training process traverses the observations to build the M+. The value is an integer that ranges from '1' to '10000'. The default value is '10'.'sgd.shuffleType' - Whether Amazon ML shuffles the training data. Shuffling the data improves a model's ability to find the optimal solution for a variety of data types. The valid values are auto and none. The default value is none3. We strongly recommend that you shuffle your data.'sgd.l1RegularizationAmount' - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L1 normalization. This parameter can't be used when L2, is specified. Use this parameter sparingly.'sgd.l2RegularizationAmount' - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as  '1.0E-08'.'The value is a double that ranges from '0' to  MAX_DOUBLEP. The default is to not use L2 normalization. This parameter can't be used when L1, is specified. Use this parameter sparingly.0A user-supplied ID that uniquely identifies the M..The category of supervised learning that this M/ will address. Choose from the following types:Choose  REGRESSION if the M) will be used to predict a numeric value.Choose BINARY if the M result has two possible values.Choose  MULTICLASS if the M' result has a limited number of values.For more information, see the  5http://docs.aws.amazon.com/machine-learning/latest/dg'Amazon Machine Learning Developer Guide.The O" that points to the training data.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the M5. This value should be identical to the value of the  MLModelId in the request.The response status code. UVWXYZ[\]^_  UVWXYZ[\]^_(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.The B operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the A parameter.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:+A user-supplied name or description of the O.The compute statistics for a OI. The statistics are generated from the observation data referenced by a O2. Amazon ML uses the statistics internally during M) training. This parameter must be set to true if the ' needs to be used for M training.8A user-supplied identifier that uniquely identifies the O.The data specification of a O:@DataLocationS3 - The Amazon S3 location of the observation data.5DataSchemaLocationS3 - The Amazon S3 location of the  DataSchema.LDataSchema - A JSON string representing the schema. This is not required if  DataSchemaUri is specified.gDataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the  Datasource.ESample - ' "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"'Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the O5. This value should be identical to the value of the  DataSourceID in the request.The response status code.`abcdefg  `abcdefg(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR Represents the output of a J operation, and is an acknowledgement that Amazon ML received the request.The B operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the A parameter.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:+A user-supplied name or description of the O.The compute statistics for a OI. The statistics are generated from the observation data referenced by a O2. Amazon ML uses the statistics internally during M) training. This parameter must be set to true if the O needs to be used for M training.0A user-supplied ID that uniquely identifies the O.-The data specification of an Amazon Redshift O:DatabaseInformation - DatabaseName, - The name of the Amazon Redshift database.' ClusterIdentifier' - The unique ID for the Amazon Redshift cluster. - DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database.QSelectSqlQuery - The query that is used to retrieve the observation data for the  Datasource.S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the SelectSqlQuery" query is stored in this location..DataSchemaUri - The Amazon S3 location of the  DataSchema.LDataSchema - A JSON string representing the schema. This is not required if  DataSchemaUri is specified.gDataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the O.ESample - ' "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"'|A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following:3A security group to allow Amazon ML to execute the SelectSqlQuery$ query on an Amazon Redshift clusterLAn Amazon S3 bucket policy to grant Amazon ML read/write permissions on the S3StagingLocationCreates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:oA user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the  DataSourceID in the request.The response status code.hijklmnop  hijklmnop(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR )Amazon ML returns the following elements.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:&The ID of the ML object. For example, exampleModelId.The type of the ML object.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:The ID of the tagged ML object.!The type of the tagged ML object.-A list of tags associated with the ML object.The response status code.qrstuvwx  qrstuvwx(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DRRepresents the output of a  operation.See:  smart constructor.See:  smart constructor.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the O.Creates a value of 4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:0A user-supplied ID that uniquely identifies the O5. This value should be identical to the value of the  DataSourceID in the request.The response status code.yz{|}yz{|}(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)None !"05DR'Represents the output of an ( operation.-You can see the updated content by using the GetBatchPrediction operation.See: , smart constructor.(See: ) smart constructor.)Creates a value of (4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:*+*The ID assigned to the O during creation.+/A new user-supplied name or description of the O+ that will replace the current description.,Creates a value of '4 with the minimum fields required to make a request.BUse one of the following lenses to modify other fields as desired:-.-The ID assigned to the OE during creation. This value should be identical to the value of the  DataSourceID in the request..The response status code.'~()*+*+,.-./0123456'()*+,-.)(*+,'-.'~()*+,-./0123456!(c) 2013-2016 Brendan HayMozilla Public License, v. 2.0.%Brendan Hay <brendan.g.hay@gmail.com>auto-generatednon-portable (GHC extensions)NoneE  !"#$%&'()*+,-.3/012456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~     *+,-./0123FGHIJKLM`abcdefghijklmnopq !"#$789:;<=>?@ABCDEFGH\]^_`abcdefghijklmnopqrstuv   !"#$%&'()*+,-./012345678KLMNOPQRefghijk~'()*+,-.\]^_>?56789:;<=./01234+,-%&'()* !"#$  PQRSTUVWXYZ[\]^_`aObcdefghijklmnopqrstNuvwxyz{|}~MLKJIHGFEDCBA@&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcRd e f g h i j k l m n o p q * ) ( ' r s t u v w x y z { | } ~  $      !"#$%"&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~%                                                           ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U # V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w xyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                                                                                                       ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u vwxywxzwx{|}~                                                    !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~'amazonka-ml-1.4.4-2yA9Z7arOzvng1YYT0XHX!Network.AWS.MachineLearning.Types/Network.AWS.MachineLearning.DescribeDataSources,Network.AWS.MachineLearning.DescribeMLModels#Network.AWS.MachineLearning.AddTags2Network.AWS.MachineLearning.CreateRealtimeEndpoint/Network.AWS.MachineLearning.DescribeEvaluations)Network.AWS.MachineLearning.GetEvaluation1Network.AWS.MachineLearning.CreateBatchPrediction2Network.AWS.MachineLearning.DeleteRealtimeEndpoint#Network.AWS.MachineLearning.Predict,Network.AWS.MachineLearning.CreateEvaluation3Network.AWS.MachineLearning.CreateDataSourceFromRDS4Network.AWS.MachineLearning.DescribeBatchPredictions#Network.AWS.MachineLearning.Waiters.Network.AWS.MachineLearning.GetBatchPrediction)Network.AWS.MachineLearning.UpdateMLModel)Network.AWS.MachineLearning.DeleteMLModel,Network.AWS.MachineLearning.DeleteEvaluation,Network.AWS.MachineLearning.UpdateEvaluation)Network.AWS.MachineLearning.GetDataSource&Network.AWS.MachineLearning.GetMLModel1Network.AWS.MachineLearning.UpdateBatchPrediction1Network.AWS.MachineLearning.DeleteBatchPrediction&Network.AWS.MachineLearning.DeleteTags)Network.AWS.MachineLearning.CreateMLModel2Network.AWS.MachineLearning.CreateDataSourceFromS38Network.AWS.MachineLearning.CreateDataSourceFromRedshift(Network.AWS.MachineLearning.DescribeTags,Network.AWS.MachineLearning.DeleteDataSource,Network.AWS.MachineLearning.UpdateDataSource%Network.AWS.MachineLearning.Types.Sum)Network.AWS.MachineLearning.Types.ProductNetwork.AWS.MachineLearningDescribeMLModelsDescribeBatchPredictionsDescribeDataSourcesDescribeEvaluationsTaggableResourceTypeBatchPrediction DataSource EvaluationMLModel SortOrderAscDscRealtimeEndpointStatusFailedNoneReadyUpdating MLModelTypeBinary Multiclass RegressionMLModelFilterVariableMLMFVAlgorithmMLMFVCreatedAt MLMFVIAMUserMLMFVLastUpdatedAtMLMFVMLModelType MLMFVNameMLMFVRealtimeEndpointStatus MLMFVStatusMLMFVTrainingDataSourceIdMLMFVTrainingDataURIEvaluationFilterVariable EvalCreatedAtEvalDataSourceId EvalDataURI EvalIAMUserEvalLastUpdatedAt EvalMLModelIdEvalName EvalStatus EntityStatus ESCompleted ESDeletedESFailed ESInprogress ESPendingDetailsAttributes AlgorithmPredictiveModelTypeDataSourceFilterVariable DataCreatedAtDataDATALOCATIONS3 DataIAMUserDataLastUpdatedAtDataName DataStatusBatchPredictionFilterVariableBatchCreatedAtBatchDataSourceId BatchDataURI BatchIAMUserBatchLastUpdatedAtBatchMLModelId BatchName BatchStatusSGDTag S3DataSpecRedshiftMetadataRedshiftDatabaseCredentialsRedshiftDatabaseRedshiftDataSpecRealtimeEndpointInfo RDSMetadataRDSDatabaseCredentials RDSDatabase RDSDataSpec PredictionPerformanceMetricsbatchPredictionbpStatusbpLastUpdatedAt bpCreatedAt bpComputeTimebpInputDataLocationS3 bpMLModelIdbpBatchPredictionDataSourceIdbpTotalRecordCount bpStartedAtbpBatchPredictionId bpFinishedAtbpInvalidRecordCountbpCreatedByIAMUserbpName bpMessage bpOutputURI dataSourcedsStatusdsNumberOfFilesdsLastUpdatedAt dsCreatedAt dsComputeTimedsDataSourceId dsRDSMetadatadsDataSizeInBytes dsStartedAt dsFinishedAtdsCreatedByIAMUserdsNamedsDataLocationS3dsComputeStatistics dsMessagedsRedshiftMetadatadsDataRearrangement dsRoleARN evaluationeStatusePerformanceMetricseLastUpdatedAt eCreatedAt eComputeTimeeInputDataLocationS3 eMLModelId eStartedAt eFinishedAteCreatedByIAMUsereName eEvaluationIdeMessageeEvaluationDataSourceIdmLModel mlmStatusmlmLastUpdatedAtmlmTrainingParametersmlmScoreThresholdLastUpdatedAt mlmCreatedAtmlmComputeTimemlmInputDataLocationS3 mlmMLModelIdmlmSizeInBytes mlmStartedAtmlmScoreThreshold mlmFinishedAt mlmAlgorithmmlmCreatedByIAMUsermlmNamemlmEndpointInfomlmTrainingDataSourceId mlmMessagemlmMLModelTypeperformanceMetrics pmProperties predictionpPredictedValuepPredictedLabelpPredictedScorespDetails rdsDataSpecrdsdsDataSchemaURIrdsdsDataSchemardsdsDataRearrangementrdsdsDatabaseInformationrdsdsSelectSqlQueryrdsdsDatabaseCredentialsrdsdsS3StagingLocationrdsdsResourceRolerdsdsServiceRole rdsdsSubnetIdrdsdsSecurityGroupIds rdsDatabaserdsdInstanceIdentifierrdsdDatabaseNamerdsDatabaseCredentials rdsdcUsername rdsdcPassword rdsMetadatarmSelectSqlQueryrmDataPipelineId rmDatabasermDatabaseUserNamermResourceRole rmServiceRolerealtimeEndpointInfo reiCreatedAtreiEndpointURLreiEndpointStatusreiPeakRequestsPerSecondredshiftDataSpecrDataSchemaURI rDataSchemarDataRearrangementrDatabaseInformationrSelectSqlQueryrDatabaseCredentialsrS3StagingLocationredshiftDatabaserdDatabaseNamerdClusterIdentifierredshiftDatabaseCredentials rdcUsername rdcPasswordredshiftMetadataredSelectSqlQueryredRedshiftDatabaseredDatabaseUserName s3DataSpec sdsDataSchemasdsDataSchemaLocationS3sdsDataRearrangementsdsDataLocationS3tagtagValuetagKeymachineLearning_InvalidTagException_InternalServerException_InvalidInputException%_IdempotentParameterMismatchException_TagLimitExceededException_PredictorNotMountedException_ResourceNotFoundException_LimitExceededExceptionDescribeDataSourcesResponsedescribeDataSourcesddsEQddsGE ddsPrefixddsGTddsNE ddsNextToken ddsSortOrderddsLimitddsLTddsFilterVariableddsLEdescribeDataSourcesResponse ddssrsResultsddssrsNextTokenddssrsResponseStatus#$fNFDataDescribeDataSourcesResponse$fToQueryDescribeDataSources$fToPathDescribeDataSources$fToJSONDescribeDataSources$fToHeadersDescribeDataSources$fNFDataDescribeDataSources$fHashableDescribeDataSources$fAWSRequestDescribeDataSources$fAWSPagerDescribeDataSources$fEqDescribeDataSources$fReadDescribeDataSources$fShowDescribeDataSources$fDataDescribeDataSources$fGenericDescribeDataSources$fEqDescribeDataSourcesResponse!$fReadDescribeDataSourcesResponse!$fShowDescribeDataSourcesResponse!$fDataDescribeDataSourcesResponse$$fGenericDescribeDataSourcesResponseDescribeMLModelsResponsedescribeMLModelsdmlmEQdmlmGE dmlmPrefixdmlmGTdmlmNE dmlmNextToken dmlmSortOrder dmlmLimitdmlmLTdmlmFilterVariabledmlmLEdescribeMLModelsResponsedmlmsrsResultsdmlmsrsNextTokendmlmsrsResponseStatus $fNFDataDescribeMLModelsResponse$fToQueryDescribeMLModels$fToPathDescribeMLModels$fToJSONDescribeMLModels$fToHeadersDescribeMLModels$fNFDataDescribeMLModels$fHashableDescribeMLModels$fAWSRequestDescribeMLModels$fAWSPagerDescribeMLModels$fEqDescribeMLModels$fReadDescribeMLModels$fShowDescribeMLModels$fDataDescribeMLModels$fGenericDescribeMLModels$fEqDescribeMLModelsResponse$fReadDescribeMLModelsResponse$fShowDescribeMLModelsResponse$fDataDescribeMLModelsResponse!$fGenericDescribeMLModelsResponseAddTagsResponseAddTagsaddTagsatTags atResourceIdatResourceTypeaddTagsResponseatrsResourceIdatrsResourceTypeatrsResponseStatus$fNFDataAddTagsResponse$fToQueryAddTags$fToPathAddTags$fToJSONAddTags$fToHeadersAddTags$fNFDataAddTags$fHashableAddTags$fAWSRequestAddTags $fEqAddTags $fReadAddTags $fShowAddTags $fDataAddTags$fGenericAddTags$fEqAddTagsResponse$fReadAddTagsResponse$fShowAddTagsResponse$fDataAddTagsResponse$fGenericAddTagsResponseCreateRealtimeEndpointResponseCreateRealtimeEndpointcreateRealtimeEndpoint creMLModelIdcreateRealtimeEndpointResponsecrersRealtimeEndpointInfocrersMLModelIdcrersResponseStatus&$fNFDataCreateRealtimeEndpointResponse$fToQueryCreateRealtimeEndpoint$fToPathCreateRealtimeEndpoint$fToJSONCreateRealtimeEndpoint!$fToHeadersCreateRealtimeEndpoint$fNFDataCreateRealtimeEndpoint $fHashableCreateRealtimeEndpoint"$fAWSRequestCreateRealtimeEndpoint$fEqCreateRealtimeEndpoint$fReadCreateRealtimeEndpoint$fShowCreateRealtimeEndpoint$fDataCreateRealtimeEndpoint$fGenericCreateRealtimeEndpoint"$fEqCreateRealtimeEndpointResponse$$fReadCreateRealtimeEndpointResponse$$fShowCreateRealtimeEndpointResponse$$fDataCreateRealtimeEndpointResponse'$fGenericCreateRealtimeEndpointResponseDescribeEvaluationsResponsedescribeEvaluationsdeEQdeGEdePrefixdeGTdeNE deNextToken deSortOrderdeLimitdeLTdeFilterVariabledeLEdescribeEvaluationsResponse desrsResultsdesrsNextTokendesrsResponseStatus#$fNFDataDescribeEvaluationsResponse$fToQueryDescribeEvaluations$fToPathDescribeEvaluations$fToJSONDescribeEvaluations$fToHeadersDescribeEvaluations$fNFDataDescribeEvaluations$fHashableDescribeEvaluations$fAWSRequestDescribeEvaluations$fAWSPagerDescribeEvaluations$fEqDescribeEvaluations$fReadDescribeEvaluations$fShowDescribeEvaluations$fDataDescribeEvaluations$fGenericDescribeEvaluations$fEqDescribeEvaluationsResponse!$fReadDescribeEvaluationsResponse!$fShowDescribeEvaluationsResponse!$fDataDescribeEvaluationsResponse$$fGenericDescribeEvaluationsResponseGetEvaluationResponse GetEvaluation getEvaluationgeEvaluationIdgetEvaluationResponse gersStatusgersPerformanceMetricsgersLastUpdatedAt gersCreatedAtgersComputeTimegersInputDataLocationS3 gersMLModelId gersStartedAtgersFinishedAtgersCreatedByIAMUsergersName gersLogURIgersEvaluationId gersMessagegersEvaluationDataSourceIdgersResponseStatus$fNFDataGetEvaluationResponse$fToQueryGetEvaluation$fToPathGetEvaluation$fToJSONGetEvaluation$fToHeadersGetEvaluation$fNFDataGetEvaluation$fHashableGetEvaluation$fAWSRequestGetEvaluation$fEqGetEvaluation$fReadGetEvaluation$fShowGetEvaluation$fDataGetEvaluation$fGenericGetEvaluation$fEqGetEvaluationResponse$fReadGetEvaluationResponse$fShowGetEvaluationResponse$fDataGetEvaluationResponse$fGenericGetEvaluationResponseCreateBatchPredictionResponseCreateBatchPredictioncreateBatchPredictioncbpBatchPredictionNamecbpBatchPredictionId cbpMLModelIdcbpBatchPredictionDataSourceId cbpOutputURIcreateBatchPredictionResponsecbprsBatchPredictionIdcbprsResponseStatus%$fNFDataCreateBatchPredictionResponse$fToQueryCreateBatchPrediction$fToPathCreateBatchPrediction$fToJSONCreateBatchPrediction $fToHeadersCreateBatchPrediction$fNFDataCreateBatchPrediction$fHashableCreateBatchPrediction!$fAWSRequestCreateBatchPrediction$fEqCreateBatchPrediction$fReadCreateBatchPrediction$fShowCreateBatchPrediction$fDataCreateBatchPrediction$fGenericCreateBatchPrediction!$fEqCreateBatchPredictionResponse#$fReadCreateBatchPredictionResponse#$fShowCreateBatchPredictionResponse#$fDataCreateBatchPredictionResponse&$fGenericCreateBatchPredictionResponseDeleteRealtimeEndpointResponseDeleteRealtimeEndpointdeleteRealtimeEndpoint dreMLModelIddeleteRealtimeEndpointResponsedrersRealtimeEndpointInfodrersMLModelIddrersResponseStatus&$fNFDataDeleteRealtimeEndpointResponse$fToQueryDeleteRealtimeEndpoint$fToPathDeleteRealtimeEndpoint$fToJSONDeleteRealtimeEndpoint!$fToHeadersDeleteRealtimeEndpoint$fNFDataDeleteRealtimeEndpoint $fHashableDeleteRealtimeEndpoint"$fAWSRequestDeleteRealtimeEndpoint$fEqDeleteRealtimeEndpoint$fReadDeleteRealtimeEndpoint$fShowDeleteRealtimeEndpoint$fDataDeleteRealtimeEndpoint$fGenericDeleteRealtimeEndpoint"$fEqDeleteRealtimeEndpointResponse$$fReadDeleteRealtimeEndpointResponse$$fShowDeleteRealtimeEndpointResponse$$fDataDeleteRealtimeEndpointResponse'$fGenericDeleteRealtimeEndpointResponsePredictResponsePredictpredict pMLModelIdpRecordpPredictEndpointpredictResponse prsPredictionprsResponseStatus$fNFDataPredictResponse$fToQueryPredict$fToPathPredict$fToJSONPredict$fToHeadersPredict$fNFDataPredict$fHashablePredict$fAWSRequestPredict $fEqPredict $fReadPredict $fShowPredict $fDataPredict$fGenericPredict$fEqPredictResponse$fReadPredictResponse$fShowPredictResponse$fDataPredictResponse$fGenericPredictResponseCreateEvaluationResponseCreateEvaluationcreateEvaluationceEvaluationNameceEvaluationId ceMLModelIdceEvaluationDataSourceIdcreateEvaluationResponsecersEvaluationIdcersResponseStatus $fNFDataCreateEvaluationResponse$fToQueryCreateEvaluation$fToPathCreateEvaluation$fToJSONCreateEvaluation$fToHeadersCreateEvaluation$fNFDataCreateEvaluation$fHashableCreateEvaluation$fAWSRequestCreateEvaluation$fEqCreateEvaluation$fReadCreateEvaluation$fShowCreateEvaluation$fDataCreateEvaluation$fGenericCreateEvaluation$fEqCreateEvaluationResponse$fReadCreateEvaluationResponse$fShowCreateEvaluationResponse$fDataCreateEvaluationResponse!$fGenericCreateEvaluationResponseCreateDataSourceFromRDSResponseCreateDataSourceFromRDScreateDataSourceFromRDScdsfrdsDataSourceNamecdsfrdsComputeStatisticscdsfrdsDataSourceIdcdsfrdsRDSDatacdsfrdsRoleARNcreateDataSourceFromRDSResponsecdsfrdsrsDataSourceIdcdsfrdsrsResponseStatus'$fNFDataCreateDataSourceFromRDSResponse $fToQueryCreateDataSourceFromRDS$fToPathCreateDataSourceFromRDS$fToJSONCreateDataSourceFromRDS"$fToHeadersCreateDataSourceFromRDS$fNFDataCreateDataSourceFromRDS!$fHashableCreateDataSourceFromRDS#$fAWSRequestCreateDataSourceFromRDS$fEqCreateDataSourceFromRDS$fReadCreateDataSourceFromRDS$fShowCreateDataSourceFromRDS$fDataCreateDataSourceFromRDS $fGenericCreateDataSourceFromRDS#$fEqCreateDataSourceFromRDSResponse%$fReadCreateDataSourceFromRDSResponse%$fShowCreateDataSourceFromRDSResponse%$fDataCreateDataSourceFromRDSResponse($fGenericCreateDataSourceFromRDSResponse DescribeBatchPredictionsResponsedescribeBatchPredictionsdbpEQdbpGE dbpPrefixdbpGTdbpNE dbpNextToken dbpSortOrderdbpLimitdbpLTdbpFilterVariabledbpLE describeBatchPredictionsResponse dbpsrsResultsdbpsrsNextTokendbpsrsResponseStatus($fNFDataDescribeBatchPredictionsResponse!$fToQueryDescribeBatchPredictions $fToPathDescribeBatchPredictions $fToJSONDescribeBatchPredictions#$fToHeadersDescribeBatchPredictions $fNFDataDescribeBatchPredictions"$fHashableDescribeBatchPredictions$$fAWSRequestDescribeBatchPredictions"$fAWSPagerDescribeBatchPredictions$fEqDescribeBatchPredictions$fReadDescribeBatchPredictions$fShowDescribeBatchPredictions$fDataDescribeBatchPredictions!$fGenericDescribeBatchPredictions$$fEqDescribeBatchPredictionsResponse&$fReadDescribeBatchPredictionsResponse&$fShowDescribeBatchPredictionsResponse&$fDataDescribeBatchPredictionsResponse)$fGenericDescribeBatchPredictionsResponsemLModelAvailablebatchPredictionAvailabledataSourceAvailableevaluationAvailableGetBatchPredictionResponseGetBatchPredictiongetBatchPredictiongbpBatchPredictionIdgetBatchPredictionResponse gbprsStatusgbprsLastUpdatedAtgbprsCreatedAtgbprsComputeTimegbprsInputDataLocationS3gbprsMLModelId gbprsBatchPredictionDataSourceIdgbprsTotalRecordCountgbprsStartedAtgbprsBatchPredictionIdgbprsFinishedAtgbprsInvalidRecordCountgbprsCreatedByIAMUser gbprsName gbprsLogURI gbprsMessagegbprsOutputURIgbprsResponseStatus"$fNFDataGetBatchPredictionResponse$fToQueryGetBatchPrediction$fToPathGetBatchPrediction$fToJSONGetBatchPrediction$fToHeadersGetBatchPrediction$fNFDataGetBatchPrediction$fHashableGetBatchPrediction$fAWSRequestGetBatchPrediction$fEqGetBatchPrediction$fReadGetBatchPrediction$fShowGetBatchPrediction$fDataGetBatchPrediction$fGenericGetBatchPrediction$fEqGetBatchPredictionResponse $fReadGetBatchPredictionResponse $fShowGetBatchPredictionResponse $fDataGetBatchPredictionResponse#$fGenericGetBatchPredictionResponseUpdateMLModelResponse UpdateMLModel updateMLModelumlmMLModelNameumlmScoreThreshold umlmMLModelIdupdateMLModelResponseumlmrsMLModelIdumlmrsResponseStatus$fNFDataUpdateMLModelResponse$fToQueryUpdateMLModel$fToPathUpdateMLModel$fToJSONUpdateMLModel$fToHeadersUpdateMLModel$fNFDataUpdateMLModel$fHashableUpdateMLModel$fAWSRequestUpdateMLModel$fEqUpdateMLModel$fReadUpdateMLModel$fShowUpdateMLModel$fDataUpdateMLModel$fGenericUpdateMLModel$fEqUpdateMLModelResponse$fReadUpdateMLModelResponse$fShowUpdateMLModelResponse$fDataUpdateMLModelResponse$fGenericUpdateMLModelResponseDeleteMLModelResponse DeleteMLModel deleteMLModel dmlmMLModelIddeleteMLModelResponsedmlmrsMLModelIddmlmrsResponseStatus$fNFDataDeleteMLModelResponse$fToQueryDeleteMLModel$fToPathDeleteMLModel$fToJSONDeleteMLModel$fToHeadersDeleteMLModel$fNFDataDeleteMLModel$fHashableDeleteMLModel$fAWSRequestDeleteMLModel$fEqDeleteMLModel$fReadDeleteMLModel$fShowDeleteMLModel$fDataDeleteMLModel$fGenericDeleteMLModel$fEqDeleteMLModelResponse$fReadDeleteMLModelResponse$fShowDeleteMLModelResponse$fDataDeleteMLModelResponse$fGenericDeleteMLModelResponseDeleteEvaluationResponseDeleteEvaluationdeleteEvaluationdeEvaluationIddeleteEvaluationResponsedersEvaluationIddersResponseStatus $fNFDataDeleteEvaluationResponse$fToQueryDeleteEvaluation$fToPathDeleteEvaluation$fToJSONDeleteEvaluation$fToHeadersDeleteEvaluation$fNFDataDeleteEvaluation$fHashableDeleteEvaluation$fAWSRequestDeleteEvaluation$fEqDeleteEvaluation$fReadDeleteEvaluation$fShowDeleteEvaluation$fDataDeleteEvaluation$fGenericDeleteEvaluation$fEqDeleteEvaluationResponse$fReadDeleteEvaluationResponse$fShowDeleteEvaluationResponse$fDataDeleteEvaluationResponse!$fGenericDeleteEvaluationResponseUpdateEvaluationResponseUpdateEvaluationupdateEvaluationueEvaluationIdueEvaluationNameupdateEvaluationResponseuersEvaluationIduersResponseStatus $fNFDataUpdateEvaluationResponse$fToQueryUpdateEvaluation$fToPathUpdateEvaluation$fToJSONUpdateEvaluation$fToHeadersUpdateEvaluation$fNFDataUpdateEvaluation$fHashableUpdateEvaluation$fAWSRequestUpdateEvaluation$fEqUpdateEvaluation$fReadUpdateEvaluation$fShowUpdateEvaluation$fDataUpdateEvaluation$fGenericUpdateEvaluation$fEqUpdateEvaluationResponse$fReadUpdateEvaluationResponse$fShowUpdateEvaluationResponse$fDataUpdateEvaluationResponse!$fGenericUpdateEvaluationResponseGetDataSourceResponse GetDataSource getDataSource gdsVerbosegdsDataSourceIdgetDataSourceResponse gdsrsStatusgdsrsNumberOfFilesgdsrsLastUpdatedAtgdsrsCreatedAtgdsrsComputeTimegdsrsDataSourceIdgdsrsRDSMetadatagdsrsDataSizeInBytesgdsrsDataSourceSchemagdsrsStartedAtgdsrsFinishedAtgdsrsCreatedByIAMUser gdsrsName gdsrsLogURIgdsrsDataLocationS3gdsrsComputeStatistics gdsrsMessagegdsrsRedshiftMetadatagdsrsDataRearrangement gdsrsRoleARNgdsrsResponseStatus$fNFDataGetDataSourceResponse$fToQueryGetDataSource$fToPathGetDataSource$fToJSONGetDataSource$fToHeadersGetDataSource$fNFDataGetDataSource$fHashableGetDataSource$fAWSRequestGetDataSource$fEqGetDataSource$fReadGetDataSource$fShowGetDataSource$fDataGetDataSource$fGenericGetDataSource$fEqGetDataSourceResponse$fReadGetDataSourceResponse$fShowGetDataSourceResponse$fDataGetDataSourceResponse$fGenericGetDataSourceResponseGetMLModelResponse GetMLModel getMLModel gmlmVerbose gmlmMLModelIdgetMLModelResponse gmlmrsStatusgmlmrsLastUpdatedAtgmlmrsTrainingParameters!gmlmrsScoreThresholdLastUpdatedAtgmlmrsCreatedAtgmlmrsComputeTime gmlmrsRecipegmlmrsInputDataLocationS3gmlmrsMLModelIdgmlmrsSizeInBytes gmlmrsSchemagmlmrsStartedAtgmlmrsScoreThresholdgmlmrsFinishedAtgmlmrsCreatedByIAMUser gmlmrsName gmlmrsLogURIgmlmrsEndpointInfogmlmrsTrainingDataSourceId gmlmrsMessagegmlmrsMLModelTypegmlmrsResponseStatus$fNFDataGetMLModelResponse$fToQueryGetMLModel$fToPathGetMLModel$fToJSONGetMLModel$fToHeadersGetMLModel$fNFDataGetMLModel$fHashableGetMLModel$fAWSRequestGetMLModel$fEqGetMLModel$fReadGetMLModel$fShowGetMLModel$fDataGetMLModel$fGenericGetMLModel$fEqGetMLModelResponse$fReadGetMLModelResponse$fShowGetMLModelResponse$fDataGetMLModelResponse$fGenericGetMLModelResponseUpdateBatchPredictionResponseUpdateBatchPredictionupdateBatchPredictionubpBatchPredictionIdubpBatchPredictionNameupdateBatchPredictionResponseubprsBatchPredictionIdubprsResponseStatus%$fNFDataUpdateBatchPredictionResponse$fToQueryUpdateBatchPrediction$fToPathUpdateBatchPrediction$fToJSONUpdateBatchPrediction $fToHeadersUpdateBatchPrediction$fNFDataUpdateBatchPrediction$fHashableUpdateBatchPrediction!$fAWSRequestUpdateBatchPrediction$fEqUpdateBatchPrediction$fReadUpdateBatchPrediction$fShowUpdateBatchPrediction$fDataUpdateBatchPrediction$fGenericUpdateBatchPrediction!$fEqUpdateBatchPredictionResponse#$fReadUpdateBatchPredictionResponse#$fShowUpdateBatchPredictionResponse#$fDataUpdateBatchPredictionResponse&$fGenericUpdateBatchPredictionResponseDeleteBatchPredictionResponseDeleteBatchPredictiondeleteBatchPredictiondbpBatchPredictionIddeleteBatchPredictionResponsedbprsBatchPredictionIddbprsResponseStatus%$fNFDataDeleteBatchPredictionResponse$fToQueryDeleteBatchPrediction$fToPathDeleteBatchPrediction$fToJSONDeleteBatchPrediction $fToHeadersDeleteBatchPrediction$fNFDataDeleteBatchPrediction$fHashableDeleteBatchPrediction!$fAWSRequestDeleteBatchPrediction$fEqDeleteBatchPrediction$fReadDeleteBatchPrediction$fShowDeleteBatchPrediction$fDataDeleteBatchPrediction$fGenericDeleteBatchPrediction!$fEqDeleteBatchPredictionResponse#$fReadDeleteBatchPredictionResponse#$fShowDeleteBatchPredictionResponse#$fDataDeleteBatchPredictionResponse&$fGenericDeleteBatchPredictionResponseDeleteTagsResponse DeleteTags deleteTagsdTagKeys dResourceId dResourceTypedeleteTagsResponse drsResourceIddrsResourceTypedrsResponseStatus$fNFDataDeleteTagsResponse$fToQueryDeleteTags$fToPathDeleteTags$fToJSONDeleteTags$fToHeadersDeleteTags$fNFDataDeleteTags$fHashableDeleteTags$fAWSRequestDeleteTags$fEqDeleteTags$fReadDeleteTags$fShowDeleteTags$fDataDeleteTags$fGenericDeleteTags$fEqDeleteTagsResponse$fReadDeleteTagsResponse$fShowDeleteTagsResponse$fDataDeleteTagsResponse$fGenericDeleteTagsResponseCreateMLModelResponse CreateMLModel createMLModel cmlmRecipe cmlmRecipeURIcmlmMLModelNamecmlmParameters cmlmMLModelIdcmlmMLModelTypecmlmTrainingDataSourceIdcreateMLModelResponsecmlmrsMLModelIdcmlmrsResponseStatus$fNFDataCreateMLModelResponse$fToQueryCreateMLModel$fToPathCreateMLModel$fToJSONCreateMLModel$fToHeadersCreateMLModel$fNFDataCreateMLModel$fHashableCreateMLModel$fAWSRequestCreateMLModel$fEqCreateMLModel$fReadCreateMLModel$fShowCreateMLModel$fDataCreateMLModel$fGenericCreateMLModel$fEqCreateMLModelResponse$fReadCreateMLModelResponse$fShowCreateMLModelResponse$fDataCreateMLModelResponse$fGenericCreateMLModelResponseCreateDataSourceFromS3ResponseCreateDataSourceFromS3createDataSourceFromS3cdsfsDataSourceNamecdsfsComputeStatisticscdsfsDataSourceId cdsfsDataSpeccreateDataSourceFromS3ResponsecdsfsrsDataSourceIdcdsfsrsResponseStatus&$fNFDataCreateDataSourceFromS3Response$fToQueryCreateDataSourceFromS3$fToPathCreateDataSourceFromS3$fToJSONCreateDataSourceFromS3!$fToHeadersCreateDataSourceFromS3$fNFDataCreateDataSourceFromS3 $fHashableCreateDataSourceFromS3"$fAWSRequestCreateDataSourceFromS3$fEqCreateDataSourceFromS3$fReadCreateDataSourceFromS3$fShowCreateDataSourceFromS3$fDataCreateDataSourceFromS3$fGenericCreateDataSourceFromS3"$fEqCreateDataSourceFromS3Response$$fReadCreateDataSourceFromS3Response$$fShowCreateDataSourceFromS3Response$$fDataCreateDataSourceFromS3Response'$fGenericCreateDataSourceFromS3Response$CreateDataSourceFromRedshiftResponseCreateDataSourceFromRedshiftcreateDataSourceFromRedshiftcdsfrDataSourceNamecdsfrComputeStatisticscdsfrDataSourceId cdsfrDataSpec cdsfrRoleARN$createDataSourceFromRedshiftResponsecdsfrrsDataSourceIdcdsfrrsResponseStatus,$fNFDataCreateDataSourceFromRedshiftResponse%$fToQueryCreateDataSourceFromRedshift$$fToPathCreateDataSourceFromRedshift$$fToJSONCreateDataSourceFromRedshift'$fToHeadersCreateDataSourceFromRedshift$$fNFDataCreateDataSourceFromRedshift&$fHashableCreateDataSourceFromRedshift($fAWSRequestCreateDataSourceFromRedshift $fEqCreateDataSourceFromRedshift"$fReadCreateDataSourceFromRedshift"$fShowCreateDataSourceFromRedshift"$fDataCreateDataSourceFromRedshift%$fGenericCreateDataSourceFromRedshift($fEqCreateDataSourceFromRedshiftResponse*$fReadCreateDataSourceFromRedshiftResponse*$fShowCreateDataSourceFromRedshiftResponse*$fDataCreateDataSourceFromRedshiftResponse-$fGenericCreateDataSourceFromRedshiftResponseDescribeTagsResponse DescribeTags describeTags dtResourceIddtResourceTypedescribeTagsResponsedtrsResourceIddtrsResourceTypedtrsTagsdtrsResponseStatus$fNFDataDescribeTagsResponse$fToQueryDescribeTags$fToPathDescribeTags$fToJSONDescribeTags$fToHeadersDescribeTags$fNFDataDescribeTags$fHashableDescribeTags$fAWSRequestDescribeTags$fEqDescribeTags$fReadDescribeTags$fShowDescribeTags$fDataDescribeTags$fGenericDescribeTags$fEqDescribeTagsResponse$fReadDescribeTagsResponse$fShowDescribeTagsResponse$fDataDescribeTagsResponse$fGenericDescribeTagsResponseDeleteDataSourceResponseDeleteDataSourcedeleteDataSourceddsDataSourceIddeleteDataSourceResponseddsrsDataSourceIdddsrsResponseStatus $fNFDataDeleteDataSourceResponse$fToQueryDeleteDataSource$fToPathDeleteDataSource$fToJSONDeleteDataSource$fToHeadersDeleteDataSource$fNFDataDeleteDataSource$fHashableDeleteDataSource$fAWSRequestDeleteDataSource$fEqDeleteDataSource$fReadDeleteDataSource$fShowDeleteDataSource$fDataDeleteDataSource$fGenericDeleteDataSource$fEqDeleteDataSourceResponse$fReadDeleteDataSourceResponse$fShowDeleteDataSourceResponse$fDataDeleteDataSourceResponse!$fGenericDeleteDataSourceResponseUpdateDataSourceResponseUpdateDataSourceupdateDataSourceudsDataSourceIdudsDataSourceNameupdateDataSourceResponseudsrsDataSourceIdudsrsResponseStatus $fNFDataUpdateDataSourceResponse$fToQueryUpdateDataSource$fToPathUpdateDataSource$fToJSONUpdateDataSource$fToHeadersUpdateDataSource$fNFDataUpdateDataSource$fHashableUpdateDataSource$fAWSRequestUpdateDataSource$fEqUpdateDataSource$fReadUpdateDataSource$fShowUpdateDataSource$fDataUpdateDataSource$fGenericUpdateDataSource$fEqUpdateDataSourceResponse$fReadUpdateDataSourceResponse$fShowUpdateDataSourceResponse$fDataUpdateDataSourceResponse!$fGenericUpdateDataSourceResponse'http-types-0.9.1-58mzFhAgNAb9DH0XYXjd5PNetwork.HTTP.Types.StatusStatus$fFromJSONTaggableResourceType$fToJSONTaggableResourceType$fToHeaderTaggableResourceType$fToQueryTaggableResourceType"$fToByteStringTaggableResourceType$fNFDataTaggableResourceType$fHashableTaggableResourceType$fToTextTaggableResourceType$fFromTextTaggableResourceType$fToJSONSortOrder$fToHeaderSortOrder$fToQuerySortOrder$fToByteStringSortOrder$fNFDataSortOrder$fHashableSortOrder$fToTextSortOrder$fFromTextSortOrder $fFromJSONRealtimeEndpointStatus $fToHeaderRealtimeEndpointStatus$fToQueryRealtimeEndpointStatus$$fToByteStringRealtimeEndpointStatus$fNFDataRealtimeEndpointStatus $fHashableRealtimeEndpointStatus$fToTextRealtimeEndpointStatus $fFromTextRealtimeEndpointStatus$fFromJSONMLModelType$fToJSONMLModelType$fToHeaderMLModelType$fToQueryMLModelType$fToByteStringMLModelType$fNFDataMLModelType$fHashableMLModelType$fToTextMLModelType$fFromTextMLModelType$fToJSONMLModelFilterVariable$fToHeaderMLModelFilterVariable$fToQueryMLModelFilterVariable#$fToByteStringMLModelFilterVariable$fNFDataMLModelFilterVariable$fHashableMLModelFilterVariable$fToTextMLModelFilterVariable$fFromTextMLModelFilterVariable $fToJSONEvaluationFilterVariable"$fToHeaderEvaluationFilterVariable!$fToQueryEvaluationFilterVariable&$fToByteStringEvaluationFilterVariable $fNFDataEvaluationFilterVariable"$fHashableEvaluationFilterVariable $fToTextEvaluationFilterVariable"$fFromTextEvaluationFilterVariable$fFromJSONEntityStatus$fToHeaderEntityStatus$fToQueryEntityStatus$fToByteStringEntityStatus$fNFDataEntityStatus$fHashableEntityStatus$fToTextEntityStatus$fFromTextEntityStatus$fFromJSONDetailsAttributes$fToHeaderDetailsAttributes$fToQueryDetailsAttributes$fToByteStringDetailsAttributes$fNFDataDetailsAttributes$fHashableDetailsAttributes$fToTextDetailsAttributes$fFromTextDetailsAttributes $fToJSONDataSourceFilterVariable"$fToHeaderDataSourceFilterVariable!$fToQueryDataSourceFilterVariable&$fToByteStringDataSourceFilterVariable $fNFDataDataSourceFilterVariable"$fHashableDataSourceFilterVariable $fToTextDataSourceFilterVariable"$fFromTextDataSourceFilterVariable%$fToJSONBatchPredictionFilterVariable'$fToHeaderBatchPredictionFilterVariable&$fToQueryBatchPredictionFilterVariable+$fToByteStringBatchPredictionFilterVariable%$fNFDataBatchPredictionFilterVariable'$fHashableBatchPredictionFilterVariable%$fToTextBatchPredictionFilterVariable'$fFromTextBatchPredictionFilterVariable$fFromJSONAlgorithm$fToHeaderAlgorithm$fToQueryAlgorithm$fToByteStringAlgorithm$fNFDataAlgorithm$fHashableAlgorithm$fToTextAlgorithm$fFromTextAlgorithmTag' _tagValue_tagKey S3DataSpec'_sdsDataSchema_sdsDataSchemaLocationS3_sdsDataRearrangement_sdsDataLocationS3RedshiftMetadata'_redSelectSqlQuery_redRedshiftDatabase_redDatabaseUserNameRedshiftDatabaseCredentials' _rdcUsername _rdcPasswordRedshiftDatabase'_rdDatabaseName_rdClusterIdentifierRedshiftDataSpec'_rDataSchemaURI _rDataSchema_rDataRearrangement_rDatabaseInformation_rSelectSqlQuery_rDatabaseCredentials_rS3StagingLocationRealtimeEndpointInfo' _reiCreatedAt_reiEndpointURL_reiEndpointStatus_reiPeakRequestsPerSecond RDSMetadata'_rmSelectSqlQuery_rmDataPipelineId _rmDatabase_rmDatabaseUserName_rmResourceRole_rmServiceRoleRDSDatabaseCredentials'_rdsdcUsername_rdsdcPassword RDSDatabase'_rdsdInstanceIdentifier_rdsdDatabaseName RDSDataSpec'_rdsdsDataSchemaURI_rdsdsDataSchema_rdsdsDataRearrangement_rdsdsDatabaseInformation_rdsdsSelectSqlQuery_rdsdsDatabaseCredentials_rdsdsS3StagingLocation_rdsdsResourceRole_rdsdsServiceRole_rdsdsSubnetId_rdsdsSecurityGroupIds Prediction'_pPredictedValue_pPredictedLabel_pPredictedScores _pDetailsPerformanceMetrics' _pmPropertiesMLModel' _mlmStatus_mlmLastUpdatedAt_mlmTrainingParameters_mlmScoreThresholdLastUpdatedAt _mlmCreatedAt_mlmComputeTime_mlmInputDataLocationS3 _mlmMLModelId_mlmSizeInBytes _mlmStartedAt_mlmScoreThreshold_mlmFinishedAt _mlmAlgorithm_mlmCreatedByIAMUser_mlmName_mlmEndpointInfo_mlmTrainingDataSourceId _mlmMessage_mlmMLModelType Evaluation'_eStatus_ePerformanceMetrics_eLastUpdatedAt _eCreatedAt _eComputeTime_eInputDataLocationS3 _eMLModelId _eStartedAt _eFinishedAt_eCreatedByIAMUser_eName_eEvaluationId _eMessage_eEvaluationDataSourceId DataSource' _dsStatus_dsNumberOfFiles_dsLastUpdatedAt _dsCreatedAt_dsComputeTime_dsDataSourceId_dsRDSMetadata_dsDataSizeInBytes _dsStartedAt _dsFinishedAt_dsCreatedByIAMUser_dsName_dsDataLocationS3_dsComputeStatistics _dsMessage_dsRedshiftMetadata_dsDataRearrangement _dsRoleARNBatchPrediction' _bpStatus_bpLastUpdatedAt _bpCreatedAt_bpComputeTime_bpInputDataLocationS3 _bpMLModelId_bpBatchPredictionDataSourceId_bpTotalRecordCount _bpStartedAt_bpBatchPredictionId _bpFinishedAt_bpInvalidRecordCount_bpCreatedByIAMUser_bpName _bpMessage _bpOutputURI $fToJSONTag $fNFDataTag $fHashableTag $fFromJSONTag$fToJSONS3DataSpec$fNFDataS3DataSpec$fHashableS3DataSpec$fNFDataRedshiftMetadata$fHashableRedshiftMetadata$fFromJSONRedshiftMetadata#$fToJSONRedshiftDatabaseCredentials#$fNFDataRedshiftDatabaseCredentials%$fHashableRedshiftDatabaseCredentials$fToJSONRedshiftDatabase$fNFDataRedshiftDatabase$fHashableRedshiftDatabase$fFromJSONRedshiftDatabase$fToJSONRedshiftDataSpec$fNFDataRedshiftDataSpec$fHashableRedshiftDataSpec$fNFDataRealtimeEndpointInfo$fHashableRealtimeEndpointInfo$fFromJSONRealtimeEndpointInfo$fNFDataRDSMetadata$fHashableRDSMetadata$fFromJSONRDSMetadata$fToJSONRDSDatabaseCredentials$fNFDataRDSDatabaseCredentials $fHashableRDSDatabaseCredentials$fToJSONRDSDatabase$fNFDataRDSDatabase$fHashableRDSDatabase$fFromJSONRDSDatabase$fToJSONRDSDataSpec$fNFDataRDSDataSpec$fHashableRDSDataSpec$fNFDataPrediction$fHashablePrediction$fFromJSONPrediction$fNFDataPerformanceMetrics$fHashablePerformanceMetrics$fFromJSONPerformanceMetrics$fNFDataMLModel$fHashableMLModel$fFromJSONMLModel$fNFDataEvaluation$fHashableEvaluation$fFromJSONEvaluation$fNFDataDataSource$fHashableDataSource$fFromJSONDataSource$fNFDataBatchPrediction$fHashableBatchPrediction$fFromJSONBatchPredictionghc-prim GHC.TypesEQGTLTDescribeDataSourcesResponse'_ddssrsResults_ddssrsNextToken_ddssrsResponseStatusDescribeDataSources'_ddsEQ_ddsGE _ddsPrefix_ddsGT_ddsNE _ddsNextToken _ddsSortOrder _ddsLimit_ddsLT_ddsFilterVariable_ddsLEDescribeMLModelsResponse'_dmlmsrsResults_dmlmsrsNextToken_dmlmsrsResponseStatusDescribeMLModels'_dmlmEQ_dmlmGE _dmlmPrefix_dmlmGT_dmlmNE_dmlmNextToken_dmlmSortOrder _dmlmLimit_dmlmLT_dmlmFilterVariable_dmlmLEAddTagsResponse'_atrsResourceId_atrsResourceType_atrsResponseStatusAddTags'_atTags _atResourceId_atResourceTypeCreateRealtimeEndpointResponse'_crersRealtimeEndpointInfo_crersMLModelId_crersResponseStatusCreateRealtimeEndpoint' _creMLModelIdDescribeEvaluationsResponse' _desrsResults_desrsNextToken_desrsResponseStatusDescribeEvaluations'_deEQ_deGE _dePrefix_deGT_deNE _deNextToken _deSortOrder_deLimit_deLT_deFilterVariable_deLEGetEvaluationResponse' _gersStatus_gersPerformanceMetrics_gersLastUpdatedAt_gersCreatedAt_gersComputeTime_gersInputDataLocationS3_gersMLModelId_gersStartedAt_gersFinishedAt_gersCreatedByIAMUser _gersName _gersLogURI_gersEvaluationId _gersMessage_gersEvaluationDataSourceId_gersResponseStatusGetEvaluation'_geEvaluationIdCreateBatchPredictionResponse'_cbprsBatchPredictionId_cbprsResponseStatusCreateBatchPrediction'_cbpBatchPredictionName_cbpBatchPredictionId _cbpMLModelId_cbpBatchPredictionDataSourceId _cbpOutputURIDeleteRealtimeEndpointResponse'_drersRealtimeEndpointInfo_drersMLModelId_drersResponseStatusDeleteRealtimeEndpoint' _dreMLModelIdPredictResponse'_prsPrediction_prsResponseStatusPredict' _pMLModelId_pRecord_pPredictEndpointCreateEvaluationResponse'_cersEvaluationId_cersResponseStatusCreateEvaluation'_ceEvaluationName_ceEvaluationId _ceMLModelId_ceEvaluationDataSourceId CreateDataSourceFromRDSResponse'_cdsfrdsrsDataSourceId_cdsfrdsrsResponseStatusCreateDataSourceFromRDS'_cdsfrdsDataSourceName_cdsfrdsComputeStatistics_cdsfrdsDataSourceId_cdsfrdsRDSData_cdsfrdsRoleARN!DescribeBatchPredictionsResponse'_dbpsrsResults_dbpsrsNextToken_dbpsrsResponseStatusDescribeBatchPredictions'_dbpEQ_dbpGE _dbpPrefix_dbpGT_dbpNE _dbpNextToken _dbpSortOrder _dbpLimit_dbpLT_dbpFilterVariable_dbpLEGetBatchPredictionResponse' _gbprsStatus_gbprsLastUpdatedAt_gbprsCreatedAt_gbprsComputeTime_gbprsInputDataLocationS3_gbprsMLModelId!_gbprsBatchPredictionDataSourceId_gbprsTotalRecordCount_gbprsStartedAt_gbprsBatchPredictionId_gbprsFinishedAt_gbprsInvalidRecordCount_gbprsCreatedByIAMUser _gbprsName _gbprsLogURI _gbprsMessage_gbprsOutputURI_gbprsResponseStatusGetBatchPrediction'_gbpBatchPredictionIdUpdateMLModelResponse'_umlmrsMLModelId_umlmrsResponseStatusUpdateMLModel'_umlmMLModelName_umlmScoreThreshold_umlmMLModelIdDeleteMLModelResponse'_dmlmrsMLModelId_dmlmrsResponseStatusDeleteMLModel'_dmlmMLModelIdDeleteEvaluationResponse'_dersEvaluationId_dersResponseStatusDeleteEvaluation'_deEvaluationIdUpdateEvaluationResponse'_uersEvaluationId_uersResponseStatusUpdateEvaluation'_ueEvaluationId_ueEvaluationNameGetDataSourceResponse' _gdsrsStatus_gdsrsNumberOfFiles_gdsrsLastUpdatedAt_gdsrsCreatedAt_gdsrsComputeTime_gdsrsDataSourceId_gdsrsRDSMetadata_gdsrsDataSizeInBytes_gdsrsDataSourceSchema_gdsrsStartedAt_gdsrsFinishedAt_gdsrsCreatedByIAMUser _gdsrsName _gdsrsLogURI_gdsrsDataLocationS3_gdsrsComputeStatistics _gdsrsMessage_gdsrsRedshiftMetadata_gdsrsDataRearrangement _gdsrsRoleARN_gdsrsResponseStatusGetDataSource' _gdsVerbose_gdsDataSourceIdGetMLModelResponse' _gmlmrsStatus_gmlmrsLastUpdatedAt_gmlmrsTrainingParameters"_gmlmrsScoreThresholdLastUpdatedAt_gmlmrsCreatedAt_gmlmrsComputeTime _gmlmrsRecipe_gmlmrsInputDataLocationS3_gmlmrsMLModelId_gmlmrsSizeInBytes _gmlmrsSchema_gmlmrsStartedAt_gmlmrsScoreThreshold_gmlmrsFinishedAt_gmlmrsCreatedByIAMUser _gmlmrsName _gmlmrsLogURI_gmlmrsEndpointInfo_gmlmrsTrainingDataSourceId_gmlmrsMessage_gmlmrsMLModelType_gmlmrsResponseStatus GetMLModel' _gmlmVerbose_gmlmMLModelIdUpdateBatchPredictionResponse'_ubprsBatchPredictionId_ubprsResponseStatusUpdateBatchPrediction'_ubpBatchPredictionId_ubpBatchPredictionNameDeleteBatchPredictionResponse'_dbprsBatchPredictionId_dbprsResponseStatusDeleteBatchPrediction'_dbpBatchPredictionIdDeleteTagsResponse'_drsResourceId_drsResourceType_drsResponseStatus DeleteTags' _dTagKeys _dResourceId_dResourceTypeCreateMLModelResponse'_cmlmrsMLModelId_cmlmrsResponseStatusCreateMLModel' _cmlmRecipe_cmlmRecipeURI_cmlmMLModelName_cmlmParameters_cmlmMLModelId_cmlmMLModelType_cmlmTrainingDataSourceIdCreateDataSourceFromS3Response'_cdsfsrsDataSourceId_cdsfsrsResponseStatusCreateDataSourceFromS3'_cdsfsDataSourceName_cdsfsComputeStatistics_cdsfsDataSourceId_cdsfsDataSpec%CreateDataSourceFromRedshiftResponse'_cdsfrrsDataSourceId_cdsfrrsResponseStatusCreateDataSourceFromRedshift'_cdsfrDataSourceName_cdsfrComputeStatistics_cdsfrDataSourceId_cdsfrDataSpec _cdsfrRoleARNDescribeTagsResponse'_dtrsResourceId_dtrsResourceType _dtrsTags_dtrsResponseStatus DescribeTags' _dtResourceId_dtResourceTypeDeleteDataSourceResponse'_ddsrsDataSourceId_ddsrsResponseStatusDeleteDataSource'_ddsDataSourceIdUpdateDataSourceResponse'_udsrsDataSourceId_udsrsResponseStatusUpdateDataSource'_udsDataSourceId_udsDataSourceName