Uses of Class
com.amazonaws.services.machinelearning.model.CreateMLModelRequest

Packages that use CreateMLModelRequest

Package	Description
com.amazonaws.services.machinelearning
com.amazonaws.services.machinelearning.model

Uses of CreateMLModelRequest in com.amazonaws.services.machinelearning

Methods in com.amazonaws.services.machinelearning with parameters of type CreateMLModelRequest

Modifier and Type	Method	Description
CreateMLModelResult	AbstractAmazonMachineLearning.createMLModel(CreateMLModelRequest request)
CreateMLModelResult	AmazonMachineLearning.createMLModel(CreateMLModelRequest createMLModelRequest)	Creates a new MLModel using the data files and the recipe as information sources.
CreateMLModelResult	AmazonMachineLearningClient.createMLModel(CreateMLModelRequest createMLModelRequest)	Creates a new MLModel using the data files and the recipe as information sources.
Future<CreateMLModelResult>	AbstractAmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest request)
Future<CreateMLModelResult>	AbstractAmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)
Future<CreateMLModelResult>	AmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest createMLModelRequest)	Creates a new MLModel using the data files and the recipe as information sources.
Future<CreateMLModelResult>	AmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)	Creates a new MLModel using the data files and the recipe as information sources.
Future<CreateMLModelResult>	AmazonMachineLearningAsyncClient.createMLModelAsync(CreateMLModelRequest request)
Future<CreateMLModelResult>	AmazonMachineLearningAsyncClient.createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)

Method parameters in com.amazonaws.services.machinelearning with type arguments of type CreateMLModelRequest

Modifier and Type	Method	Description
Future<CreateMLModelResult>	AbstractAmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)
Future<CreateMLModelResult>	AmazonMachineLearningAsync.createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)	Creates a new MLModel using the data files and the recipe as information sources.
Future<CreateMLModelResult>	AmazonMachineLearningAsyncClient.createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest, CreateMLModelResult> asyncHandler)

Uses of CreateMLModelRequest in com.amazonaws.services.machinelearning.model

Methods in com.amazonaws.services.machinelearning.model that return CreateMLModelRequest

Modifier and Type	Method	Description
CreateMLModelRequest	CreateMLModelRequest.addParametersEntry(String key, String value)
CreateMLModelRequest	CreateMLModelRequest.clearParametersEntries()	Removes all the entries added into Parameters.
CreateMLModelRequest	CreateMLModelRequest.clone()
CreateMLModelRequest	CreateMLModelRequest.withMLModelId(String mLModelId)	A user-supplied ID that uniquely identifies the MLModel.
CreateMLModelRequest	CreateMLModelRequest.withMLModelName(String mLModelName)	A user-supplied name or description of the MLModel.
CreateMLModelRequest	CreateMLModelRequest.withMLModelType(MLModelType mLModelType)	The category of supervised learning that this MLModel will address.
CreateMLModelRequest	CreateMLModelRequest.withMLModelType(String mLModelType)	The category of supervised learning that this MLModel will address.
CreateMLModelRequest	CreateMLModelRequest.withParameters(Map<String,String> parameters)	A list of the training parameters in the MLModel.
CreateMLModelRequest	CreateMLModelRequest.withRecipe(String recipe)	The data recipe for creating MLModel.
CreateMLModelRequest	CreateMLModelRequest.withRecipeUri(String recipeUri)	The Amazon Simple Storage Service (Amazon S3) location and file name that contains the MLModel recipe.
CreateMLModelRequest	CreateMLModelRequest.withTrainingDataSourceId(String trainingDataSourceId)	The DataSource that points to the training data.