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

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

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

Methods in com.amazonaws.services.machinelearning that return GetMLModelResult
`GetMLModelResult` AmazonMachineLearningClient.`getMLModel(GetMLModelRequest getMLModelRequest)` Returns an `MLModel` that includes detailed metadata, data source information, and the current status of the `MLModel`.
`GetMLModelResult` AmazonMachineLearning.`getMLModel(GetMLModelRequest getMLModelRequest)` Returns an `MLModel` that includes detailed metadata, data source information, and the current status of the `MLModel`.
`GetMLModelResult` AbstractAmazonMachineLearning.`getMLModel(GetMLModelRequest request)`

Methods in com.amazonaws.services.machinelearning that return types with arguments of type GetMLModelResult
`Future<GetMLModelResult>` AbstractAmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest request)`
`Future<GetMLModelResult>` AmazonMachineLearningAsyncClient.`getMLModelAsync(GetMLModelRequest request)`
`Future<GetMLModelResult>` AmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest getMLModelRequest)` Returns an `MLModel` that includes detailed metadata, data source information, and the current status of the `MLModel`.
`Future<GetMLModelResult>` AbstractAmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest request, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)`
`Future<GetMLModelResult>` AmazonMachineLearningAsyncClient.`getMLModelAsync(GetMLModelRequest request, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)`
`Future<GetMLModelResult>` AmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest getMLModelRequest, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)` Returns an `MLModel` that includes detailed metadata, data source information, and the current status of the `MLModel`.

Method parameters in com.amazonaws.services.machinelearning with type arguments of type GetMLModelResult
`Future<GetMLModelResult>` AbstractAmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest request, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)`
`Future<GetMLModelResult>` AmazonMachineLearningAsyncClient.`getMLModelAsync(GetMLModelRequest request, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)`
`Future<GetMLModelResult>` AmazonMachineLearningAsync.`getMLModelAsync(GetMLModelRequest getMLModelRequest, AsyncHandler<GetMLModelRequest,GetMLModelResult> asyncHandler)` Returns an `MLModel` that includes detailed metadata, data source information, and the current status of the `MLModel`.

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

Methods in com.amazonaws.services.machinelearning.model that return GetMLModelResult
`GetMLModelResult` GetMLModelResult.`addTrainingParametersEntry(String key, String value)`
`GetMLModelResult` GetMLModelResult.`clearTrainingParametersEntries()` Removes all the entries added into TrainingParameters.
`GetMLModelResult` GetMLModelResult.`clone()`
`GetMLModelResult` GetMLModelResult.`withComputeTime(Long computeTime)` The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the `MLModel`, normalized and scaled on computation resources.
`GetMLModelResult` GetMLModelResult.`withCreatedAt(Date createdAt)` The time that the `MLModel` was created.
`GetMLModelResult` GetMLModelResult.`withCreatedByIamUser(String createdByIamUser)` The AWS user account from which the `MLModel` was created.
`GetMLModelResult` GetMLModelResult.`withEndpointInfo(RealtimeEndpointInfo endpointInfo)` The current endpoint of the `MLModel`
`GetMLModelResult` GetMLModelResult.`withFinishedAt(Date finishedAt)` The epoch time when Amazon Machine Learning marked the `MLModel` as `COMPLETED` or `FAILED`.
`GetMLModelResult` GetMLModelResult.`withInputDataLocationS3(String inputDataLocationS3)` The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
`GetMLModelResult` GetMLModelResult.`withLastUpdatedAt(Date lastUpdatedAt)` The time of the most recent edit to the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withLogUri(String logUri)` A link to the file that contains logs of the `CreateMLModel` operation.
`GetMLModelResult` GetMLModelResult.`withMessage(String message)` A description of the most recent details about accessing the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withMLModelId(String mLModelId)` The MLModel ID, which is same as the `MLModelId` in the request.
`GetMLModelResult` GetMLModelResult.`withMLModelType(MLModelType mLModelType)` Identifies the `MLModel` category.
`GetMLModelResult` GetMLModelResult.`withMLModelType(String mLModelType)` Identifies the `MLModel` category.
`GetMLModelResult` GetMLModelResult.`withName(String name)` A user-supplied name or description of the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withRecipe(String recipe)` The recipe to use when training the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withSchema(String schema)` The schema used by all of the data files referenced by the `DataSource`.
`GetMLModelResult` GetMLModelResult.`withScoreThreshold(Float scoreThreshold)` The scoring threshold is used in binary classification `MLModel` models.
`GetMLModelResult` GetMLModelResult.`withScoreThresholdLastUpdatedAt(Date scoreThresholdLastUpdatedAt)` The time of the most recent edit to the `ScoreThreshold`.
`GetMLModelResult` GetMLModelResult.`withSizeInBytes(Long sizeInBytes)`
`GetMLModelResult` GetMLModelResult.`withStartedAt(Date startedAt)` The epoch time when Amazon Machine Learning marked the `MLModel` as `INPROGRESS`.
`GetMLModelResult` GetMLModelResult.`withStatus(EntityStatus status)` The current status of the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withStatus(String status)` The current status of the `MLModel`.
`GetMLModelResult` GetMLModelResult.`withTrainingDataSourceId(String trainingDataSourceId)` The ID of the training `DataSource`.
`GetMLModelResult` GetMLModelResult.`withTrainingParameters(Map<String,String> trainingParameters)` A list of the training parameters in the `MLModel`.