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Paws::MachineLearning:UseraContributed)Paws::MachineLearning::CreateMLModel(3)

NAME
       Paws::MachineLearning::CreateMLModel - Arguments	for method
       CreateMLModel on	Paws::MachineLearning

DESCRIPTION
       This class represents the parameters used for calling the method
       CreateMLModel on	the Amazon Machine Learning service. Use the
       attributes of this class	as arguments to	method CreateMLModel.

       You shouln't make instances of this class. Each attribute should	be
       used as a named argument	in the call to CreateMLModel.

       As an example:

	 $service_obj->CreateMLModel(Att1 => $value1, Att2 => $value2, ...);

       Values for attributes that are native types (Int, String, Float,	etc)
       can passed as-is	(scalar	values). Values	for complex Types (objects)
       can be passed as	a HashRef. The keys and	values of the hashref will be
       used to instance	the underlying object.

ATTRIBUTES
   REQUIRED MLModelId => Str
       A user-supplied ID that uniquely	identifies the "MLModel".

   MLModelName => Str
       A user-supplied name or description of the "MLModel".

   REQUIRED MLModelType	=> Str
       The category of supervised learning that	this "MLModel" will address.
       Choose from the following types:

       o   Choose "REGRESSION" if the "MLModel"	will be	used to	predict	a
	   numeric value.

       o   Choose "BINARY" if the "MLModel" result has two possible values.

       o   Choose "MULTICLASS" if the "MLModel"	result has a limited number of
	   values.

       For more	information, see the Amazon Machine Learning Developer Guide.

   Parameters => Paws::MachineLearning::TrainingParameters
       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:

       o   "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.

       o   "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.

       o   "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.

       o   "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.

   Recipe => Str
       The data	recipe for creating "MLModel". You must	specify	either the
       recipe or its URI. If you donAcAAt specify a recipe or its URI, Amazon
       ML creates a default.

   RecipeUri =>	Str
       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 donAcAAt specify a recipe or its URI,	Amazon ML
       creates a default.

   REQUIRED TrainingDataSourceId => Str
       The "DataSource"	that points to the training data.

SEE ALSO
       This class forms	part of	Paws, documenting arguments for	method
       CreateMLModel in	Paws::MachineLearning

BUGS and CONTRIBUTIONS
       The source code is located here:	https://github.com/pplu/aws-sdk-perl

       Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues

perl v5.24.1			  2015-Paws::MachineLearning::CreateMLModel(3)

NAME | DESCRIPTION | ATTRIBUTES | SEE ALSO | BUGS and CONTRIBUTIONS

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