Copyright | (c) 2013-2015 Brendan Hay |
---|---|
License | Mozilla Public License, v. 2.0. |
Maintainer | Brendan Hay <brendan.g.hay@gmail.com> |
Stability | auto-generated |
Portability | non-portable (GHC extensions) |
Safe Haskell | None |
Language | Haskell2010 |
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.
See: AWS API Reference for CreateMLModel.
- createMLModel :: Text -> MLModelType -> Text -> CreateMLModel
- data CreateMLModel
- cmlmRecipe :: Lens' CreateMLModel (Maybe Text)
- cmlmRecipeURI :: Lens' CreateMLModel (Maybe Text)
- cmlmMLModelName :: Lens' CreateMLModel (Maybe Text)
- cmlmParameters :: Lens' CreateMLModel (HashMap Text Text)
- cmlmMLModelId :: Lens' CreateMLModel Text
- cmlmMLModelType :: Lens' CreateMLModel MLModelType
- cmlmTrainingDataSourceId :: Lens' CreateMLModel Text
- createMLModelResponse :: Int -> CreateMLModelResponse
- data CreateMLModelResponse
- cmlmrsMLModelId :: Lens' CreateMLModelResponse (Maybe Text)
- cmlmrsResponseStatus :: Lens' CreateMLModelResponse Int
Creating a Request
Creates a value of CreateMLModel
with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
data CreateMLModel Source
See: createMLModel
smart constructor.
Request Lenses
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.
cmlmMLModelName :: Lens' CreateMLModel (Maybe Text) Source
A user-supplied name or description of the MLModel
.
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.
cmlmMLModelId :: Lens' CreateMLModel Text Source
A user-supplied ID that uniquely identifies 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 theMLModel
will be used to predict a numeric value. - Choose
BINARY
if theMLModel
result has two possible values. - Choose
MULTICLASS
if theMLModel
result has a limited number of values.
For more information, see the Amazon Machine Learning Developer Guide.
cmlmTrainingDataSourceId :: Lens' CreateMLModel Text Source
The DataSource
that points to the training data.
Destructuring the Response
Creates a value of CreateMLModelResponse
with the minimum fields required to make a request.
Use one of the following lenses to modify other fields as desired:
data CreateMLModelResponse Source
Represents the output of a CreateMLModel operation, and is an acknowledgement that Amazon ML received the request.
The CreateMLModel operation is asynchronous. You can poll for status
updates by using the GetMLModel operation and checking the Status
parameter.
See: createMLModelResponse
smart constructor.
Response Lenses
cmlmrsMLModelId :: 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.
cmlmrsResponseStatus :: Lens' CreateMLModelResponse Int Source
The response status code.