MachineLearningClient
Definition of the public APIs exposed by Amazon Machine Learning
Functions
Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you add a tag using a key that is already associated with the ML object, AddTags updates the tag's value.
Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a DataSource. This operation creates a new BatchPrediction, and uses an MLModel and the data files referenced by the DataSource as information sources.
Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a DataSource from a database hosted on an Amazon Redshift cluster. A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource. Like a DataSource for an MLModel, the DataSource for an Evaluation contains values for the Target Variable. The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType: BINARY, REGRESSION or MULTICLASS.
Creates a new MLModel using the DataSource and the recipe as information sources.
Creates a real-time endpoint for the MLModel. The endpoint contains the URI of the MLModel; that is, the location to send real-time prediction requests for the specified MLModel.
Assigns the DELETED status to a BatchPrediction, rendering it unusable.
Assigns the DELETED status to a DataSource, rendering it unusable.
Assigns the DELETED status to an Evaluation, rendering it unusable.
Assigns the DELETED status to an MLModel, rendering it unusable.
Deletes a real time endpoint of an MLModel.
Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags.
Returns a list of BatchPrediction operations that match the search criteria in the request.
Returns a list of DataSource that match the search criteria in the request.
Returns a list of DescribeEvaluations that match the search criteria in the request.
Returns a list of MLModel that match the search criteria in the request.
Describes one or more of the tags for your Amazon ML object.
Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.
Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource.
Returns an Evaluation that includes metadata as well as the current status of the Evaluation.
Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel.
Generates a prediction for the observation using the specified ML Model.
Updates the BatchPredictionName of a BatchPrediction.
Updates the DataSourceName of a DataSource.
Updates the EvaluationName of an Evaluation.
Updates the MLModelName and the ScoreThreshold of an MLModel.
Inherited functions
Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value. If you add a tag using a key that is already associated with the ML object, AddTags updates the tag's value.
Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a DataSource. This operation creates a new BatchPrediction, and uses an MLModel and the data files referenced by the DataSource as information sources.
Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a DataSource from a database hosted on an Amazon Redshift cluster. A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.
Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set of observations associated to a DataSource. Like a DataSource for an MLModel, the DataSource for an Evaluation contains values for the Target Variable. The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType: BINARY, REGRESSION or MULTICLASS.
Creates a new MLModel using the DataSource and the recipe as information sources.
Creates a real-time endpoint for the MLModel. The endpoint contains the URI of the MLModel; that is, the location to send real-time prediction requests for the specified MLModel.
Assigns the DELETED status to a BatchPrediction, rendering it unusable.
Assigns the DELETED status to a DataSource, rendering it unusable.
Assigns the DELETED status to an Evaluation, rendering it unusable.
Assigns the DELETED status to an MLModel, rendering it unusable.
Deletes a real time endpoint of an MLModel.
Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags.
Returns a list of BatchPrediction operations that match the search criteria in the request.
Paginate over DescribeBatchPredictionsResponse results.
Returns a list of DataSource that match the search criteria in the request.
Paginate over DescribeDataSourcesResponse results.
Returns a list of DescribeEvaluations that match the search criteria in the request.
Paginate over DescribeEvaluationsResponse results.
Returns a list of MLModel that match the search criteria in the request.
Paginate over DescribeMlModelsResponse results.
Describes one or more of the tags for your Amazon ML object.
Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.
Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource.
Returns an Evaluation that includes metadata as well as the current status of the Evaluation.
Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel.
Generates a prediction for the observation using the specified ML Model.
Updates the BatchPredictionName of a BatchPrediction.
Updates the DataSourceName of a DataSource.
Updates the EvaluationName of an Evaluation.
Updates the MLModelName and the ScoreThreshold of an MLModel.
Create a copy of the client with one or more configuration values overridden. This method allows the caller to perform scoped config overrides for one or more client operations.