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Name | Description | |
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BatchPrediction |
Represents the output of GetBatchPrediction operation.
The content consists of the detailed metadata, the status, and the data file information of a Batch Prediction. |
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CreateBatchPredictionRequest |
Container for the parameters to the CreateBatchPrediction operation.
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.
You can poll for status updates by using the GetBatchPrediction operation and
checking the |
|
CreateBatchPredictionResponse | Configuration for accessing Amazon CreateBatchPrediction service | |
CreateBatchPredictionResult |
Represents the output of a CreateBatchPrediction operation, and is an acknowledgement
that Amazon ML received the request.
The CreateBatchPrediction operation is asynchronous. You can poll for status
updates by using the GetBatchPrediction operation and checking the |
|
CreateDataSourceFromRDSRequest |
Container for the parameters to the CreateDataSourceFromRDS operation.
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.
If Amazon ML cannot accept the input source, it sets the |
|
CreateDataSourceFromRDSResponse | Configuration for accessing Amazon CreateDataSourceFromRDS service | |
CreateDataSourceFromRDSResult |
Represents the output of a CreateDataSourceFromRDS operation, and is an acknowledgement
that Amazon ML received the request.
The CreateDataSourceFromRDS operation is asynchronous. You can poll for updates
by using the GetBatchPrediction operation and checking the |
|
CreateDataSourceFromRedshiftRequest |
Container for the parameters to the CreateDataSourceFromRedshift operation.
Creates a DataSource from Amazon
Redshift. A DataSource references data that can be used to perform
either CreateMLModel, CreateEvaluation or CreateBatchPrediction
operations.
If Amazon ML cannot accept the input source, it sets the
The observations should exist in the database hosted on an Amazon Redshift cluster
and should be specified by a
After the |
|
CreateDataSourceFromRedshiftResponse | Configuration for accessing Amazon CreateDataSourceFromRedshift service | |
CreateDataSourceFromRedshiftResult |
Represents the output of a CreateDataSourceFromRedshift operation, and is
an acknowledgement that Amazon ML received the request.
The CreateDataSourceFromRedshift operation is asynchronous. You can poll for
updates by using the GetBatchPrediction operation and checking the |
|
CreateDataSourceFromS3Request |
Container for the parameters to the CreateDataSourceFromS3 operation.
Creates a DataSource object. A DataSource references data
that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction
operations.
If Amazon ML cannot accept the input source, it sets the
The observation data used in a
After the |
|
CreateDataSourceFromS3Response | Configuration for accessing Amazon CreateDataSourceFromS3 service | |
CreateDataSourceFromS3Result |
Represents the output of a CreateDataSourceFromS3 operation, and is an acknowledgement
that Amazon ML received the request.
The CreateDataSourceFromS3 operation is asynchronous. You can poll for updates
by using the GetBatchPrediction operation and checking the |
|
CreateEvaluationRequest |
Container for the parameters to the CreateEvaluation operation.
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 .
You can use the GetEvaluation operation to check progress of the evaluation during the creation operation. |
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CreateEvaluationResponse | Configuration for accessing Amazon CreateEvaluation service | |
CreateEvaluationResult |
Represents the output of a CreateEvaluation operation, and is an acknowledgement
that Amazon ML received the request.
CreateEvaluation operation is asynchronous. You can poll for status updates
by using the GetEvaluation operation and checking the |
|
CreateMLModelRequest |
Container for the parameters to the CreateMLModel operation.
Creates a new MLModel using the data files and the recipe as information
sources.
An
You can use the GetMLModel operation to check progress of the CreateMLModel requires a |
|
CreateMLModelResponse | Configuration for accessing Amazon CreateMLModel service | |
CreateMLModelResult |
Represents the output of a CreateMLModel operation, and is an acknowledgement
that Amazon ML received the request.
The CreateMLModel operation is asynchronous. You can poll for status updates
by using the GetMLModel operation and checking the |
|
CreateRealtimeEndpointRequest |
Container for the parameters to the CreateRealtimeEndpoint operation.
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 .
|
|
CreateRealtimeEndpointResponse | Configuration for accessing Amazon CreateRealtimeEndpoint service | |
CreateRealtimeEndpointResult |
Represents the output of an CreateRealtimeEndpoint operation.
The result contains the
The endpoint information includes the URI of the |
|
DataSource |
Represents the output of the GetDataSource operation.
The content consists of the detailed metadata and data file information and the current
status of the |
|
DeleteBatchPredictionRequest |
Container for the parameters to the DeleteBatchPrediction operation.
Assigns the DELETED status to a BatchPrediction , rendering it unusable.
After using the Caution: The result of the |
|
DeleteBatchPredictionResponse | Configuration for accessing Amazon DeleteBatchPrediction service | |
DeleteBatchPredictionResult |
Represents the output of a DeleteBatchPrediction operation.
You can use the GetBatchPrediction operation and check the value of the |
|
DeleteDataSourceRequest |
Container for the parameters to the DeleteDataSource operation.
Assigns the DELETED status to a DataSource , rendering it unusable.
After using the Caution: The results of the |
|
DeleteDataSourceResponse | Configuration for accessing Amazon DeleteDataSource service | |
DeleteDataSourceResult | Represents the output of a DeleteDataSource operation. | |
DeleteEvaluationRequest |
Container for the parameters to the DeleteEvaluation operation.
Assigns the DELETED status to an Evaluation , rendering it
unusable.
After invoking the Caution: The results of the |
|
DeleteEvaluationResponse | Configuration for accessing Amazon DeleteEvaluation service | |
DeleteEvaluationResult |
Represents the output of a DeleteEvaluation operation. The output indicates
that Amazon Machine Learning (Amazon ML) received the request.
You can use the GetEvaluation operation and check the value of the |
|
DeleteMLModelRequest |
Container for the parameters to the DeleteMLModel operation.
Assigns the DELETED status to an MLModel , rendering it unusable.
After using the Caution: The result of the |
|
DeleteMLModelResponse | Configuration for accessing Amazon DeleteMLModel service | |
DeleteMLModelResult |
Represents the output of a DeleteMLModel operation.
You can use the GetMLModel operation and check the value of the |
|
DeleteRealtimeEndpointRequest |
Container for the parameters to the DeleteRealtimeEndpoint operation.
Deletes a real time endpoint of an MLModel .
|
|
DeleteRealtimeEndpointResponse | Configuration for accessing Amazon DeleteRealtimeEndpoint service | |
DeleteRealtimeEndpointResult |
Represents the output of an DeleteRealtimeEndpoint operation.
The result contains the |
|
DescribeBatchPredictionsRequest |
Container for the parameters to the DescribeBatchPredictions operation.
Returns a list of BatchPrediction operations that match the search criteria
in the request.
|
|
DescribeBatchPredictionsResponse | Configuration for accessing Amazon DescribeBatchPredictions service | |
DescribeBatchPredictionsResult |
Represents the output of a DescribeBatchPredictions operation. The content
is essentially a list of BatchPrediction s.
|
|
DescribeDataSourcesRequest |
Container for the parameters to the DescribeDataSources operation.
Returns a list of DataSource that match the search criteria in the request.
|
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DescribeDataSourcesResponse | Configuration for accessing Amazon DescribeDataSources service | |
DescribeDataSourcesResult |
Represents the query results from a DescribeDataSources operation. The content
is essentially a list of DataSource .
|
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DescribeEvaluationsRequest |
Container for the parameters to the DescribeEvaluations operation.
Returns a list of DescribeEvaluations that match the search criteria
in the request.
|
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DescribeEvaluationsResponse | Configuration for accessing Amazon DescribeEvaluations service | |
DescribeEvaluationsResult |
Represents the query results from a DescribeEvaluations operation. The content
is essentially a list of Evaluation .
|
|
DescribeMLModelsRequest |
Container for the parameters to the DescribeMLModels operation.
Returns a list of MLModel that match the search criteria in the request.
|
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DescribeMLModelsResponse | Configuration for accessing Amazon DescribeMLModels service | |
DescribeMLModelsResult |
Represents the output of a DescribeMLModels operation. The content is essentially
a list of MLModel .
|
|
Evaluation |
Represents the output of GetEvaluation operation.
The content consists of the detailed metadata and data file information and the current
status of the |
|
GetBatchPredictionRequest |
Container for the parameters to the GetBatchPrediction operation.
Returns a BatchPrediction that includes detailed metadata, status, and
data file information for a Batch Prediction request.
|
|
GetBatchPredictionResponse | Configuration for accessing Amazon GetBatchPrediction service | |
GetBatchPredictionResult |
Represents the output of a GetBatchPrediction operation and describes a BatchPrediction .
|
|
GetDataSourceRequest |
Container for the parameters to the GetDataSource operation.
Returns a DataSource that includes metadata and data file information,
as well as the current status of the DataSource .
|
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GetDataSourceResponse | Configuration for accessing Amazon GetDataSource service | |
GetDataSourceResult |
Represents the output of a GetDataSource operation and describes a DataSource .
|
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GetEvaluationRequest |
Container for the parameters to the GetEvaluation operation.
Returns an Evaluation that includes metadata as well as the current status
of the Evaluation .
|
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GetEvaluationResponse | Configuration for accessing Amazon GetEvaluation service | |
GetEvaluationResult |
Represents the output of a GetEvaluation operation and describes an Evaluation .
|
|
GetMLModelRequest |
Container for the parameters to the GetMLModel operation.
Returns an MLModel that includes detailed metadata, and data source information
as well as the current status of the MLModel .
|
|
GetMLModelResponse | Configuration for accessing Amazon GetMLModel service | |
GetMLModelResult |
Represents the output of a GetMLModel operation, and provides detailed information
about a MLModel .
|
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IdempotentParameterMismatchException | MachineLearning exception | |
InternalServerException | MachineLearning exception | |
InvalidInputException | MachineLearning exception | |
LimitExceededException | MachineLearning exception | |
MLModel |
Represents the output of a GetMLModel operation.
The content consists of the detailed metadata and the current status of the |
|
PerformanceMetrics |
Measurements of how well the MLModel performed on known observations.
One of the following metrics is returned, based on the type of the MLModel :
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide. |
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Prediction |
The output from a Predict operation:
|
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PredictorNotMountedException | MachineLearning exception | |
PredictRequest |
Container for the parameters to the Predict operation.
Generates a prediction for the observation using the specified ML Model .
Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested. |
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PredictResponse | Configuration for accessing Amazon Predict service | |
PredictResult | ||
RDSDatabase | The database details of an Amazon RDS database. | |
RDSDatabaseCredentials | The database credentials to connect to a database on an RDS DB instance. | |
RDSDataSpec |
The data specification of an Amazon Relational Database Service (Amazon RDS) DataSource .
|
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RDSMetadata | The datasource details that are specific to Amazon RDS. | |
RealtimeEndpointInfo |
Describes the real-time endpoint information for an MLModel .
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RedshiftDatabase | Describes the database details required to connect to an Amazon Redshift database. | |
RedshiftDatabaseCredentials | Describes the database credentials for connecting to a database on an Amazon Redshift cluster. | |
RedshiftDataSpec |
Describes the data specification of an Amazon Redshift DataSource .
|
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RedshiftMetadata |
Describes the DataSource details specific to Amazon Redshift.
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ResourceNotFoundException | MachineLearning exception | |
S3DataSpec |
Describes the data specification of a DataSource .
|
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UpdateBatchPredictionRequest |
Container for the parameters to the UpdateBatchPrediction operation.
Updates the BatchPredictionName of a BatchPrediction .
You can use the GetBatchPrediction operation to view the contents of the updated data element. |
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UpdateBatchPredictionResponse | Configuration for accessing Amazon UpdateBatchPrediction service | |
UpdateBatchPredictionResult |
Represents the output of an UpdateBatchPrediction operation.
You can see the updated content by using the GetBatchPrediction operation. |
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UpdateDataSourceRequest |
Container for the parameters to the UpdateDataSource operation.
Updates the DataSourceName of a DataSource .
You can use the GetDataSource operation to view the contents of the updated data element. |
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UpdateDataSourceResponse | Configuration for accessing Amazon UpdateDataSource service | |
UpdateDataSourceResult |
Represents the output of an UpdateDataSource operation.
You can see the updated content by using the GetBatchPrediction operation. |
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UpdateEvaluationRequest |
Container for the parameters to the UpdateEvaluation operation.
Updates the EvaluationName of an Evaluation .
You can use the GetEvaluation operation to view the contents of the updated data element. |
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UpdateEvaluationResponse | Configuration for accessing Amazon UpdateEvaluation service | |
UpdateEvaluationResult |
Represents the output of an UpdateEvaluation operation.
You can see the updated content by using the GetEvaluation operation. |
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UpdateMLModelRequest |
Container for the parameters to the UpdateMLModel operation.
Updates the MLModelName and the ScoreThreshold of an MLModel .
You can use the GetMLModel operation to view the contents of the updated data element. |
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UpdateMLModelResponse | Configuration for accessing Amazon UpdateMLModel service | |
UpdateMLModelResult |
Represents the output of an UpdateMLModel operation.
You can see the updated content by using the GetMLModel operation. |