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Definition of the public APIs exposed by Amazon Machine Learning
If you’re using the service, you’re probably looking for MachineLearningClient and MachineLearning.
Structs§
- AddTags
Input - AddTags
Output Amazon ML returns the following elements.
- Batch
Prediction Represents the output of a
GetBatchPredictionoperation.The content consists of the detailed metadata, the status, and the data file information of a
Batch Prediction.- Create
Batch Prediction Input - Create
Batch Prediction Output Represents the output of a
CreateBatchPredictionoperation, and is an acknowledgement that Amazon ML received the request.The
CreateBatchPredictionoperation is asynchronous. You can poll for status updates by using the>GetBatchPredictionoperation and checking theStatusparameter of the result.- Create
Data Source FromRDS Input - Create
Data Source FromRDS Output Represents the output of a
CreateDataSourceFromRDSoperation, and is an acknowledgement that Amazon ML received the request.The
CreateDataSourceFromRDS> operation is asynchronous. You can poll for updates by using theGetBatchPredictionoperation and checking theStatusparameter. You can inspect theMessagewhenStatusshows up asFAILED. You can also check the progress of the copy operation by going to theDataPipelineconsole and looking up the pipeline using thepipelineIdfrom the describe call.- Create
Data Source From Redshift Input - Create
Data Source From Redshift Output Represents the output of a
CreateDataSourceFromRedshiftoperation, and is an acknowledgement that Amazon ML received the request.The
CreateDataSourceFromRedshiftoperation is asynchronous. You can poll for updates by using theGetBatchPredictionoperation and checking theStatusparameter.- Create
Data Source From S3Input - Create
Data Source From S3Output Represents the output of a
CreateDataSourceFromS3operation, and is an acknowledgement that Amazon ML received the request.The
CreateDataSourceFromS3operation is asynchronous. You can poll for updates by using theGetBatchPredictionoperation and checking theStatusparameter.- Create
Evaluation Input - Create
Evaluation Output Represents the output of a
CreateEvaluationoperation, and is an acknowledgement that Amazon ML received the request.CreateEvaluationoperation is asynchronous. You can poll for status updates by using theGetEvcaluationoperation and checking theStatusparameter.- CreateML
Model Input - CreateML
Model Output Represents the output of a
CreateMLModeloperation, and is an acknowledgement that Amazon ML received the request.The
CreateMLModeloperation is asynchronous. You can poll for status updates by using theGetMLModeloperation and checking theStatusparameter.- Create
Realtime Endpoint Input - Create
Realtime Endpoint Output Represents the output of an
CreateRealtimeEndpointoperation.The result contains the
MLModelIdand the endpoint information for theMLModel.The endpoint information includes the URI of the
MLModel; that is, the location to send online prediction requests for the specifiedMLModel.- Data
Source Represents the output of the
GetDataSourceoperation.The content consists of the detailed metadata and data file information and the current status of the
DataSource.- Delete
Batch Prediction Input - Delete
Batch Prediction Output Represents the output of a
DeleteBatchPredictionoperation.You can use the
GetBatchPredictionoperation and check the value of theStatusparameter to see whether aBatchPredictionis marked asDELETED.- Delete
Data Source Input - Delete
Data Source Output Represents the output of a
DeleteDataSourceoperation.- Delete
Evaluation Input - Delete
Evaluation Output Represents the output of a
DeleteEvaluationoperation. The output indicates that Amazon Machine Learning (Amazon ML) received the request.You can use the
GetEvaluationoperation and check the value of theStatusparameter to see whether anEvaluationis marked asDELETED.- DeleteML
Model Input - DeleteML
Model Output Represents the output of a
DeleteMLModeloperation.You can use the
GetMLModeloperation and check the value of theStatusparameter to see whether anMLModelis marked asDELETED.- Delete
Realtime Endpoint Input - Delete
Realtime Endpoint Output Represents the output of an
DeleteRealtimeEndpointoperation.The result contains the
MLModelIdand the endpoint information for theMLModel.- Delete
Tags Input - Delete
Tags Output Amazon ML returns the following elements.
- Describe
Batch Predictions Input - Describe
Batch Predictions Output Represents the output of a
DescribeBatchPredictionsoperation. The content is essentially a list ofBatchPredictions.- Describe
Data Sources Input - Describe
Data Sources Output Represents the query results from a DescribeDataSources operation. The content is essentially a list of
DataSource.- Describe
Evaluations Input - Describe
Evaluations Output Represents the query results from a
DescribeEvaluationsoperation. The content is essentially a list ofEvaluation.- DescribeML
Models Input - DescribeML
Models Output Represents the output of a
DescribeMLModelsoperation. The content is essentially a list ofMLModel.- Describe
Tags Input - Describe
Tags Output Amazon ML returns the following elements.
- Evaluation
Represents the output of
GetEvaluationoperation.The content consists of the detailed metadata and data file information and the current status of the
Evaluation.- GetBatch
Prediction Input - GetBatch
Prediction Output Represents the output of a
GetBatchPredictionoperation and describes aBatchPrediction.- GetData
Source Input - GetData
Source Output Represents the output of a
GetDataSourceoperation and describes aDataSource.- GetEvaluation
Input - GetEvaluation
Output Represents the output of a
GetEvaluationoperation and describes anEvaluation.- GetML
Model Input - GetML
Model Output Represents the output of a
GetMLModeloperation, and provides detailed information about aMLModel.- MLModel
Represents the output of a
GetMLModeloperation.The content consists of the detailed metadata and the current status of the
MLModel.- Machine
Learning Client - A client for the Amazon Machine Learning API.
- Performance
Metrics Measurements of how well the
MLModelperformed on known observations. One of the following metrics is returned, based on the type of theMLModel:-
BinaryAUC: The binary
MLModeluses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: The regression
MLModeluses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. -
MulticlassAvgFScore: The multiclass
MLModeluses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
-
- Predict
Input - Predict
Output - Prediction
The output from a
Predictoperation:-
Details- Contains the following attributes:DetailsAttributes.PREDICTIVEMODELTYPE - REGRESSION | BINARY | MULTICLASSDetailsAttributes.ALGORITHM - SGD -
PredictedLabel- Present for either aBINARYorMULTICLASSMLModelrequest. -
PredictedScores- Contains the raw classification score corresponding to each label. -
PredictedValue- Present for aREGRESSIONMLModelrequest.
-
- RDSData
Spec The data specification of an Amazon Relational Database Service (Amazon RDS)
DataSource.- RDSDatabase
The database details of an Amazon RDS database.
- RDSDatabase
Credentials The database credentials to connect to a database on an RDS DB instance.
- RDSMetadata
The datasource details that are specific to Amazon RDS.
- Realtime
Endpoint Info Describes the real-time endpoint information for an
MLModel.- Redshift
Data Spec Describes the data specification of an Amazon Redshift
DataSource.- Redshift
Database Describes the database details required to connect to an Amazon Redshift database.
- Redshift
Database Credentials Describes the database credentials for connecting to a database on an Amazon Redshift cluster.
- Redshift
Metadata Describes the
DataSourcedetails specific to Amazon Redshift.- S3Data
Spec Describes the data specification of a
DataSource.- Tag
A custom key-value pair associated with an ML object, such as an ML model.
- Update
Batch Prediction Input - Update
Batch Prediction Output Represents the output of an
UpdateBatchPredictionoperation.You can see the updated content by using the
GetBatchPredictionoperation.- Update
Data Source Input - Update
Data Source Output Represents the output of an
UpdateDataSourceoperation.You can see the updated content by using the
GetBatchPredictionoperation.- Update
Evaluation Input - Update
Evaluation Output Represents the output of an
UpdateEvaluationoperation.You can see the updated content by using the
GetEvaluationoperation.- UpdateML
Model Input - UpdateML
Model Output Represents the output of an
UpdateMLModeloperation.You can see the updated content by using the
GetMLModeloperation.
Enums§
- AddTags
Error - Errors returned by AddTags
- Create
Batch Prediction Error - Errors returned by CreateBatchPrediction
- Create
Data Source FromRDS Error - Errors returned by CreateDataSourceFromRDS
- Create
Data Source From Redshift Error - Errors returned by CreateDataSourceFromRedshift
- Create
Data Source From S3Error - Errors returned by CreateDataSourceFromS3
- Create
Evaluation Error - Errors returned by CreateEvaluation
- CreateML
Model Error - Errors returned by CreateMLModel
- Create
Realtime Endpoint Error - Errors returned by CreateRealtimeEndpoint
- Delete
Batch Prediction Error - Errors returned by DeleteBatchPrediction
- Delete
Data Source Error - Errors returned by DeleteDataSource
- Delete
Evaluation Error - Errors returned by DeleteEvaluation
- DeleteML
Model Error - Errors returned by DeleteMLModel
- Delete
Realtime Endpoint Error - Errors returned by DeleteRealtimeEndpoint
- Delete
Tags Error - Errors returned by DeleteTags
- Describe
Batch Predictions Error - Errors returned by DescribeBatchPredictions
- Describe
Data Sources Error - Errors returned by DescribeDataSources
- Describe
Evaluations Error - Errors returned by DescribeEvaluations
- DescribeML
Models Error - Errors returned by DescribeMLModels
- Describe
Tags Error - Errors returned by DescribeTags
- GetBatch
Prediction Error - Errors returned by GetBatchPrediction
- GetData
Source Error - Errors returned by GetDataSource
- GetEvaluation
Error - Errors returned by GetEvaluation
- GetML
Model Error - Errors returned by GetMLModel
- Predict
Error - Errors returned by Predict
- Update
Batch Prediction Error - Errors returned by UpdateBatchPrediction
- Update
Data Source Error - Errors returned by UpdateDataSource
- Update
Evaluation Error - Errors returned by UpdateEvaluation
- UpdateML
Model Error - Errors returned by UpdateMLModel
Traits§
- Machine
Learning - Trait representing the capabilities of the Amazon Machine Learning API. Amazon Machine Learning clients implement this trait.