MachineLearning class

Definition of the public APIs exposed by Amazon Machine Learning

Constructors

MachineLearning({@required String region, AwsClientCredentials credentials, Client client, String endpointUrl})

Properties

hashCode int
The hash code for this object. [...]
read-only, inherited
runtimeType Type
A representation of the runtime type of the object.
read-only, inherited

Methods

addTags({String resourceId, TaggableResourceType resourceType, List<Tag> tags}) Future<AddTagsOutput>
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. [...]
createBatchPrediction({String batchPredictionDataSourceId, String batchPredictionId, String mLModelId, String outputUri, String batchPredictionName}) Future<CreateBatchPredictionOutput>
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. [...]
createDataSourceFromRDS({String dataSourceId, RDSDataSpec rDSData, String roleARN, bool computeStatistics, String dataSourceName}) Future<CreateDataSourceFromRDSOutput>
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. [...]
createDataSourceFromRedshift({String dataSourceId, RedshiftDataSpec dataSpec, String roleARN, bool computeStatistics, String dataSourceName}) Future<CreateDataSourceFromRedshiftOutput>
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. [...]
createDataSourceFromS3({String dataSourceId, S3DataSpec dataSpec, bool computeStatistics, String dataSourceName}) Future<CreateDataSourceFromS3Output>
Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations. [...]
createEvaluation({String evaluationDataSourceId, String evaluationId, String mLModelId, String evaluationName}) Future<CreateEvaluationOutput>
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. [...]
createMLModel({String mLModelId, MLModelType mLModelType, String trainingDataSourceId, String mLModelName, Map<String, String> parameters, String recipe, String recipeUri}) Future<CreateMLModelOutput>
Creates a new MLModel using the DataSource and the recipe as information sources. [...]
createRealtimeEndpoint({String mLModelId}) Future<CreateRealtimeEndpointOutput>
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. [...]
deleteBatchPrediction({String batchPredictionId}) Future<DeleteBatchPredictionOutput>
Assigns the DELETED status to a BatchPrediction, rendering it unusable. [...]
deleteDataSource({String dataSourceId}) Future<DeleteDataSourceOutput>
Assigns the DELETED status to a DataSource, rendering it unusable. [...]
deleteEvaluation({String evaluationId}) Future<DeleteEvaluationOutput>
Assigns the DELETED status to an Evaluation, rendering it unusable. [...]
deleteMLModel({String mLModelId}) Future<DeleteMLModelOutput>
Assigns the DELETED status to an MLModel, rendering it unusable. [...]
deleteRealtimeEndpoint({String mLModelId}) Future<DeleteRealtimeEndpointOutput>
Deletes a real time endpoint of an MLModel. [...]
deleteTags({String resourceId, TaggableResourceType resourceType, List<String> tagKeys}) Future<DeleteTagsOutput>
Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags. [...]
describeBatchPredictions({String eq, BatchPredictionFilterVariable filterVariable, String ge, String gt, String le, String lt, int limit, String ne, String nextToken, String prefix, SortOrder sortOrder}) Future<DescribeBatchPredictionsOutput>
Returns a list of BatchPrediction operations that match the search criteria in the request. [...]
describeDataSources({String eq, DataSourceFilterVariable filterVariable, String ge, String gt, String le, String lt, int limit, String ne, String nextToken, String prefix, SortOrder sortOrder}) Future<DescribeDataSourcesOutput>
Returns a list of DataSource that match the search criteria in the request. [...]
describeEvaluations({String eq, EvaluationFilterVariable filterVariable, String ge, String gt, String le, String lt, int limit, String ne, String nextToken, String prefix, SortOrder sortOrder}) Future<DescribeEvaluationsOutput>
Returns a list of DescribeEvaluations that match the search criteria in the request. [...]
describeMLModels({String eq, MLModelFilterVariable filterVariable, String ge, String gt, String le, String lt, int limit, String ne, String nextToken, String prefix, SortOrder sortOrder}) Future<DescribeMLModelsOutput>
Returns a list of MLModel that match the search criteria in the request. [...]
describeTags({String resourceId, TaggableResourceType resourceType}) Future<DescribeTagsOutput>
Describes one or more of the tags for your Amazon ML object. [...]
getBatchPrediction({String batchPredictionId}) Future<GetBatchPredictionOutput>
Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request. [...]
getDataSource({String dataSourceId, bool verbose}) Future<GetDataSourceOutput>
Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource. [...]
getEvaluation({String evaluationId}) Future<GetEvaluationOutput>
Returns an Evaluation that includes metadata as well as the current status of the Evaluation. [...]
getMLModel({String mLModelId, bool verbose}) Future<GetMLModelOutput>
Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel. [...]
noSuchMethod(Invocation invocation) → dynamic
Invoked when a non-existent method or property is accessed. [...]
inherited
predict({String mLModelId, String predictEndpoint, Map<String, String> record}) Future<PredictOutput>
Generates a prediction for the observation using the specified ML Model. [...]
toString() String
A string representation of this object. [...]
inherited
updateBatchPrediction({String batchPredictionId, String batchPredictionName}) Future<UpdateBatchPredictionOutput>
Updates the BatchPredictionName of a BatchPrediction. [...]
updateDataSource({String dataSourceId, String dataSourceName}) Future<UpdateDataSourceOutput>
Updates the DataSourceName of a DataSource. [...]
updateEvaluation({String evaluationId, String evaluationName}) Future<UpdateEvaluationOutput>
Updates the EvaluationName of an Evaluation. [...]
updateMLModel({String mLModelId, String mLModelName, double scoreThreshold}) Future<UpdateMLModelOutput>
Updates the MLModelName and the ScoreThreshold of an MLModel. [...]

Operators

operator ==(Object other) bool
The equality operator. [...]
inherited