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

Packages that use CreateMLModelRequest
com.amazonaws.services.machinelearning: Definition of the public APIs exposed by Amazon Machine Learning
com.amazonaws.services.machinelearning.model

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

Methods in com.amazonaws.services.machinelearning with parameters of type CreateMLModelRequest
`CreateMLModelResult` AmazonMachineLearningClient.`createMLModel(CreateMLModelRequest createMLModelRequest)` Creates a new `MLModel` using the `DataSource` and the recipe as information sources.
`CreateMLModelResult` AmazonMachineLearning.`createMLModel(CreateMLModelRequest createMLModelRequest)` Creates a new `MLModel` using the `DataSource` and the recipe as information sources.
`CreateMLModelResult` AbstractAmazonMachineLearning.`createMLModel(CreateMLModelRequest request)`
`Future<CreateMLModelResult>` AbstractAmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest request)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsyncClient.`createMLModelAsync(CreateMLModelRequest request)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest createMLModelRequest)` Creates a new `MLModel` using the `DataSource` and the recipe as information sources.
`Future<CreateMLModelResult>` AbstractAmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsyncClient.`createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)` Creates a new `MLModel` using the `DataSource` and the recipe as information sources.

Method parameters in com.amazonaws.services.machinelearning with type arguments of type CreateMLModelRequest
`Future<CreateMLModelResult>` AbstractAmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsyncClient.`createMLModelAsync(CreateMLModelRequest request, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)`
`Future<CreateMLModelResult>` AmazonMachineLearningAsync.`createMLModelAsync(CreateMLModelRequest createMLModelRequest, AsyncHandler<CreateMLModelRequest,CreateMLModelResult> asyncHandler)` Creates a new `MLModel` using the `DataSource` and the recipe as information sources.

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

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