amazonka-ml-0.3.4: Amazon Machine Learning SDK.

Safe HaskellNone
LanguageHaskell2010

Network.AWS.MachineLearning.CreateMLModel

Contents

Description

Creates a new MLModel using the data files and the recipe as information sources.

An MLModel is nearly immutable. Users can only update the MLModelName and the ScoreThreshold in an MLModel without creating a new MLModel.

CreateMLModel is an asynchronous operation. In response to CreateMLModel, Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel status to PENDING. After the MLModel is created and ready for use, Amazon ML sets the status to COMPLETED.

You can use the GetMLModel operation to check progress of the MLModel during the creation operation.

CreateMLModel requires a DataSource with computed statistics, which can be created by setting ComputeStatistics to true in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.

http://http://docs.aws.amazon.com/machine-learning/latest/APIReference/API_CreateMLModel.html

Synopsis

Request

data CreateMLModel Source

Instances

Request constructor

createMLModel Source

Arguments

:: Text

cmlmMLModelId

-> MLModelType

cmlmMLModelType

-> Text

cmlmTrainingDataSourceId

-> CreateMLModel 

CreateMLModel constructor.

The fields accessible through corresponding lenses are:

Request lenses

cmlmMLModelId :: Lens' CreateMLModel Text Source

A user-supplied ID that uniquely identifies the MLModel.

cmlmMLModelName :: Lens' CreateMLModel (Maybe Text) Source

A user-supplied name or description of the MLModel.

cmlmMLModelType :: Lens' CreateMLModel MLModelType Source

The category of supervised learning that this MLModel will address. Choose from the following types:

Choose REGRESSION if the MLModel will be used to predict a numeric value. Choose BINARY if the MLModel result has two possible values. Choose MULTICLASS if the MLModel result has a limited number of values. For more information, see the Amazon Machine Learning Developer Guide.

cmlmParameters :: Lens' CreateMLModel (HashMap Text Text) Source

A list of the training parameters in the MLModel. The list is implemented as a map of key/value pairs.

The following is the current set of training parameters:

'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This 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_DOUBLE. The default is not to use L1 normalization. The parameter cannot be used when L2 is specified. Use this parameter sparingly.

'sgd.l2RegularizationAmount' - 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 valuseis a double that ranges from 0 to MAX_DOUBLE. The default is not to use L2 normalization. This cannot be used when L1 is specified. Use this parameter sparingly.

'sgd.maxPasses' - Number of times that the training process traverses the observations to build the MLModel. The value is an integer that ranges from 1 to 10000. The default value is 10.

'sgd.maxMLModelSizeInBytes' - 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.

cmlmRecipe :: Lens' CreateMLModel (Maybe Text) Source

The data recipe for creating MLModel. You must specify either the recipe or its URI. If you don’t specify a recipe or its URI, Amazon ML creates a default.

cmlmRecipeUri :: Lens' CreateMLModel (Maybe Text) Source

The Amazon Simple Storage Service (Amazon S3) location and file name that contains the MLModel 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.

cmlmTrainingDataSourceId :: Lens' CreateMLModel Text Source

The DataSource that points to the training data.

Response

data CreateMLModelResponse Source

Instances

Response constructor

createMLModelResponse :: CreateMLModelResponse Source

CreateMLModelResponse constructor.

The fields accessible through corresponding lenses are:

Response lenses

cmlmrMLModelId :: Lens' CreateMLModelResponse (Maybe Text) Source

A user-supplied ID that uniquely identifies the MLModel. This value should be identical to the value of the MLModelId in the request.