AWS SDK for Go (PILOT)
API Reference

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MachineLearning

import "github.com/aws/aws-sdk-go/service/machinelearning"

type MachineLearning struct { *client.Client }

MachineLearning provides the API operation methods for making requests to Amazon Machine Learning. See this package's package overview docs for details on the service.

MachineLearning methods are safe to use concurrently. It is not safe to modify mutate any of the struct's properties though.

Client

Type: *client.Client

Method

AddTags

func (c *MachineLearning) AddTags(input *AddTagsInput) (*AddTagsOutput, error)

AddTags API operation for Amazon Machine Learning.

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.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation AddTags for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInvalidTagException "InvalidTagException"

  • ErrCodeTagLimitExceededException "TagLimitExceededException"

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

AddTagsRequest

func (c *MachineLearning) AddTagsRequest(input *AddTagsInput) (req *request.Request, output *AddTagsOutput)

AddTagsRequest generates a "aws/request.Request" representing the client's request for the AddTags operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See AddTags for more information on using the AddTags API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the AddTagsRequest method. req, resp := client.AddTagsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

AddTagsWithContext

func (c *MachineLearning) AddTagsWithContext(ctx aws.Context, input *AddTagsInput, opts ...request.Option) (*AddTagsOutput, error)

AddTagsWithContext is the same as AddTags with the addition of the ability to pass a context and additional request options.

See AddTags for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateBatchPrediction

func (c *MachineLearning) CreateBatchPrediction(input *CreateBatchPredictionInput) (*CreateBatchPredictionOutput, error)

CreateBatchPrediction API operation for Amazon Machine Learning.

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.

CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction, Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction status to PENDING. After the BatchPrediction completes, Amazon ML sets the status to COMPLETED.

You can poll for status updates by using the GetBatchPrediction operation and checking the Status parameter of the result. After the COMPLETED status appears, the results are available in the location specified by the OutputUri parameter.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateBatchPrediction for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateBatchPredictionRequest

func (c *MachineLearning) CreateBatchPredictionRequest(input *CreateBatchPredictionInput) (req *request.Request, output *CreateBatchPredictionOutput)

CreateBatchPredictionRequest generates a "aws/request.Request" representing the client's request for the CreateBatchPrediction operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateBatchPrediction for more information on using the CreateBatchPrediction API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateBatchPredictionRequest method. req, resp := client.CreateBatchPredictionRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateBatchPredictionWithContext

func (c *MachineLearning) CreateBatchPredictionWithContext(ctx aws.Context, input *CreateBatchPredictionInput, opts ...request.Option) (*CreateBatchPredictionOutput, error)

CreateBatchPredictionWithContext is the same as CreateBatchPrediction with the addition of the ability to pass a context and additional request options.

See CreateBatchPrediction for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRDS

func (c *MachineLearning) CreateDataSourceFromRDS(input *CreateDataSourceFromRDSInput) (*CreateDataSourceFromRDSOutput, error)

CreateDataSourceFromRDS API operation for Amazon Machine Learning.

Creates a DataSource object from an Amazon Relational Database Service (https://aws.amazon.com/rds/) (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or PENDING state can be used only to perform >CreateMLModel>, CreateEvaluation, or CreateBatchPrediction operations.

If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateDataSourceFromRDS for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRDSRequest

func (c *MachineLearning) CreateDataSourceFromRDSRequest(input *CreateDataSourceFromRDSInput) (req *request.Request, output *CreateDataSourceFromRDSOutput)

CreateDataSourceFromRDSRequest generates a "aws/request.Request" representing the client's request for the CreateDataSourceFromRDS operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateDataSourceFromRDS for more information on using the CreateDataSourceFromRDS API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateDataSourceFromRDSRequest method. req, resp := client.CreateDataSourceFromRDSRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRDSWithContext

func (c *MachineLearning) CreateDataSourceFromRDSWithContext(ctx aws.Context, input *CreateDataSourceFromRDSInput, opts ...request.Option) (*CreateDataSourceFromRDSOutput, error)

CreateDataSourceFromRDSWithContext is the same as CreateDataSourceFromRDS with the addition of the ability to pass a context and additional request options.

See CreateDataSourceFromRDS for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRedshift

func (c *MachineLearning) CreateDataSourceFromRedshift(input *CreateDataSourceFromRedshiftInput) (*CreateDataSourceFromRedshiftOutput, error)

CreateDataSourceFromRedshift API operation for Amazon Machine Learning.

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.

CreateDataSourceFromRedshift is an asynchronous operation. In response to CreateDataSourceFromRedshift, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in COMPLETED or PENDING states can be used to perform only CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

If Amazon ML can't accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

The observations should be contained in the database hosted on an Amazon Redshift cluster and should be specified by a SelectSqlQuery query. Amazon ML executes an Unload command in Amazon Redshift to transfer the result set of the SelectSqlQuery query to S3StagingLocation.

After the DataSource has been created, it's ready for use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource also requires a recipe. A recipe describes how each input variable will be used in training an MLModel. Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it be combined with another variable or will it be split apart into word combinations? The recipe provides answers to these questions.

You can't change an existing datasource, but you can copy and modify the settings from an existing Amazon Redshift datasource to create a new datasource. To do so, call GetDataSource for an existing datasource and copy the values to a CreateDataSource call. Change the settings that you want to change and make sure that all required fields have the appropriate values.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateDataSourceFromRedshift for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRedshiftRequest

func (c *MachineLearning) CreateDataSourceFromRedshiftRequest(input *CreateDataSourceFromRedshiftInput) (req *request.Request, output *CreateDataSourceFromRedshiftOutput)

CreateDataSourceFromRedshiftRequest generates a "aws/request.Request" representing the client's request for the CreateDataSourceFromRedshift operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateDataSourceFromRedshift for more information on using the CreateDataSourceFromRedshift API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateDataSourceFromRedshiftRequest method. req, resp := client.CreateDataSourceFromRedshiftRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromRedshiftWithContext

func (c *MachineLearning) CreateDataSourceFromRedshiftWithContext(ctx aws.Context, input *CreateDataSourceFromRedshiftInput, opts ...request.Option) (*CreateDataSourceFromRedshiftOutput, error)

CreateDataSourceFromRedshiftWithContext is the same as CreateDataSourceFromRedshift with the addition of the ability to pass a context and additional request options.

See CreateDataSourceFromRedshift for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromS3

func (c *MachineLearning) CreateDataSourceFromS3(input *CreateDataSourceFromS3Input) (*CreateDataSourceFromS3Output, error)

CreateDataSourceFromS3 API operation for Amazon Machine Learning.

Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING. After the DataSource has been created and is ready for use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or PENDING state can be used to perform only CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.

If Amazon ML can't accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more .csv files in an Amazon Simple Storage Service (Amazon S3) location, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource.

After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel, the DataSource also needs a recipe. A recipe describes how each input variable will be used in training an MLModel. Will the variable be included or excluded from training? Will the variable be manipulated; for example, will it be combined with another variable or will it be split apart into word combinations? The recipe provides answers to these questions.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateDataSourceFromS3 for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromS3Request

func (c *MachineLearning) CreateDataSourceFromS3Request(input *CreateDataSourceFromS3Input) (req *request.Request, output *CreateDataSourceFromS3Output)

CreateDataSourceFromS3Request generates a "aws/request.Request" representing the client's request for the CreateDataSourceFromS3 operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateDataSourceFromS3 for more information on using the CreateDataSourceFromS3 API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateDataSourceFromS3Request method. req, resp := client.CreateDataSourceFromS3Request(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateDataSourceFromS3WithContext

func (c *MachineLearning) CreateDataSourceFromS3WithContext(ctx aws.Context, input *CreateDataSourceFromS3Input, opts ...request.Option) (*CreateDataSourceFromS3Output, error)

CreateDataSourceFromS3WithContext is the same as CreateDataSourceFromS3 with the addition of the ability to pass a context and additional request options.

See CreateDataSourceFromS3 for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateEvaluation

func (c *MachineLearning) CreateEvaluation(input *CreateEvaluationInput) (*CreateEvaluationOutput, error)

CreateEvaluation API operation for Amazon Machine Learning.

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.

CreateEvaluation is an asynchronous operation. In response to CreateEvaluation, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING. After the Evaluation is created and ready for use, Amazon ML sets the status to COMPLETED.

You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateEvaluation for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateEvaluationRequest

func (c *MachineLearning) CreateEvaluationRequest(input *CreateEvaluationInput) (req *request.Request, output *CreateEvaluationOutput)

CreateEvaluationRequest generates a "aws/request.Request" representing the client's request for the CreateEvaluation operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateEvaluation for more information on using the CreateEvaluation API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateEvaluationRequest method. req, resp := client.CreateEvaluationRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateEvaluationWithContext

func (c *MachineLearning) CreateEvaluationWithContext(ctx aws.Context, input *CreateEvaluationInput, opts ...request.Option) (*CreateEvaluationOutput, error)

CreateEvaluationWithContext is the same as CreateEvaluation with the addition of the ability to pass a context and additional request options.

See CreateEvaluation for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateMLModel

func (c *MachineLearning) CreateMLModel(input *CreateMLModelInput) (*CreateMLModelOutput, error)

CreateMLModel API operation for Amazon Machine Learning.

Creates a new MLModel using the DataSource and the recipe as information sources.

An MLModel is nearly immutable. Users can update only the MLModelName and the ScoreThreshold in an MLModel without creating a new MLModel.

CreateMLModel is an asynchronous operation. In response to CreateMLModel, Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel status to PENDING. After the MLModel has been created and ready is for use, Amazon ML sets the status to COMPLETED.

You can use the GetMLModel operation to check the progress of the MLModel during the creation operation.

CreateMLModel requires a DataSource with computed statistics, which can be created by setting ComputeStatistics to true in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateMLModel for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodeIdempotentParameterMismatchException "IdempotentParameterMismatchException" A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request.

See Also

For more information about using this API, see AWS API Documentation.

CreateMLModelRequest

func (c *MachineLearning) CreateMLModelRequest(input *CreateMLModelInput) (req *request.Request, output *CreateMLModelOutput)

CreateMLModelRequest generates a "aws/request.Request" representing the client's request for the CreateMLModel operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateMLModel for more information on using the CreateMLModel API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateMLModelRequest method. req, resp := client.CreateMLModelRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateMLModelWithContext

func (c *MachineLearning) CreateMLModelWithContext(ctx aws.Context, input *CreateMLModelInput, opts ...request.Option) (*CreateMLModelOutput, error)

CreateMLModelWithContext is the same as CreateMLModel with the addition of the ability to pass a context and additional request options.

See CreateMLModel for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

CreateRealtimeEndpoint

func (c *MachineLearning) CreateRealtimeEndpoint(input *CreateRealtimeEndpointInput) (*CreateRealtimeEndpointOutput, error)

CreateRealtimeEndpoint API operation for Amazon Machine Learning.

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.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation CreateRealtimeEndpoint for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

CreateRealtimeEndpointRequest

func (c *MachineLearning) CreateRealtimeEndpointRequest(input *CreateRealtimeEndpointInput) (req *request.Request, output *CreateRealtimeEndpointOutput)

CreateRealtimeEndpointRequest generates a "aws/request.Request" representing the client's request for the CreateRealtimeEndpoint operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See CreateRealtimeEndpoint for more information on using the CreateRealtimeEndpoint API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the CreateRealtimeEndpointRequest method. req, resp := client.CreateRealtimeEndpointRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

CreateRealtimeEndpointWithContext

func (c *MachineLearning) CreateRealtimeEndpointWithContext(ctx aws.Context, input *CreateRealtimeEndpointInput, opts ...request.Option) (*CreateRealtimeEndpointOutput, error)

CreateRealtimeEndpointWithContext is the same as CreateRealtimeEndpoint with the addition of the ability to pass a context and additional request options.

See CreateRealtimeEndpoint for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteBatchPrediction

func (c *MachineLearning) DeleteBatchPrediction(input *DeleteBatchPredictionInput) (*DeleteBatchPredictionOutput, error)

DeleteBatchPrediction API operation for Amazon Machine Learning.

Assigns the DELETED status to a BatchPrediction, rendering it unusable.

After using the DeleteBatchPrediction operation, you can use the GetBatchPrediction operation to verify that the status of the BatchPrediction changed to DELETED.

Caution: The result of the DeleteBatchPrediction operation is irreversible.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteBatchPrediction for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteBatchPredictionRequest

func (c *MachineLearning) DeleteBatchPredictionRequest(input *DeleteBatchPredictionInput) (req *request.Request, output *DeleteBatchPredictionOutput)

DeleteBatchPredictionRequest generates a "aws/request.Request" representing the client's request for the DeleteBatchPrediction operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteBatchPrediction for more information on using the DeleteBatchPrediction API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteBatchPredictionRequest method. req, resp := client.DeleteBatchPredictionRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteBatchPredictionWithContext

func (c *MachineLearning) DeleteBatchPredictionWithContext(ctx aws.Context, input *DeleteBatchPredictionInput, opts ...request.Option) (*DeleteBatchPredictionOutput, error)

DeleteBatchPredictionWithContext is the same as DeleteBatchPrediction with the addition of the ability to pass a context and additional request options.

See DeleteBatchPrediction for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteDataSource

func (c *MachineLearning) DeleteDataSource(input *DeleteDataSourceInput) (*DeleteDataSourceOutput, error)

DeleteDataSource API operation for Amazon Machine Learning.

Assigns the DELETED status to a DataSource, rendering it unusable.

After using the DeleteDataSource operation, you can use the GetDataSource operation to verify that the status of the DataSource changed to DELETED.

Caution: The results of the DeleteDataSource operation are irreversible.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteDataSource for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteDataSourceRequest

func (c *MachineLearning) DeleteDataSourceRequest(input *DeleteDataSourceInput) (req *request.Request, output *DeleteDataSourceOutput)

DeleteDataSourceRequest generates a "aws/request.Request" representing the client's request for the DeleteDataSource operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteDataSource for more information on using the DeleteDataSource API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteDataSourceRequest method. req, resp := client.DeleteDataSourceRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteDataSourceWithContext

func (c *MachineLearning) DeleteDataSourceWithContext(ctx aws.Context, input *DeleteDataSourceInput, opts ...request.Option) (*DeleteDataSourceOutput, error)

DeleteDataSourceWithContext is the same as DeleteDataSource with the addition of the ability to pass a context and additional request options.

See DeleteDataSource for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteEvaluation

func (c *MachineLearning) DeleteEvaluation(input *DeleteEvaluationInput) (*DeleteEvaluationOutput, error)

DeleteEvaluation API operation for Amazon Machine Learning.

Assigns the DELETED status to an Evaluation, rendering it unusable.

After invoking the DeleteEvaluation operation, you can use the GetEvaluation operation to verify that the status of the Evaluation changed to DELETED.

CautionThe results of the DeleteEvaluation operation are irreversible.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteEvaluation for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteEvaluationRequest

func (c *MachineLearning) DeleteEvaluationRequest(input *DeleteEvaluationInput) (req *request.Request, output *DeleteEvaluationOutput)

DeleteEvaluationRequest generates a "aws/request.Request" representing the client's request for the DeleteEvaluation operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteEvaluation for more information on using the DeleteEvaluation API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteEvaluationRequest method. req, resp := client.DeleteEvaluationRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteEvaluationWithContext

func (c *MachineLearning) DeleteEvaluationWithContext(ctx aws.Context, input *DeleteEvaluationInput, opts ...request.Option) (*DeleteEvaluationOutput, error)

DeleteEvaluationWithContext is the same as DeleteEvaluation with the addition of the ability to pass a context and additional request options.

See DeleteEvaluation for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteMLModel

func (c *MachineLearning) DeleteMLModel(input *DeleteMLModelInput) (*DeleteMLModelOutput, error)

DeleteMLModel API operation for Amazon Machine Learning.

Assigns the DELETED status to an MLModel, rendering it unusable.

After using the DeleteMLModel operation, you can use the GetMLModel operation to verify that the status of the MLModel changed to DELETED.

Caution: The result of the DeleteMLModel operation is irreversible.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteMLModel for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteMLModelRequest

func (c *MachineLearning) DeleteMLModelRequest(input *DeleteMLModelInput) (req *request.Request, output *DeleteMLModelOutput)

DeleteMLModelRequest generates a "aws/request.Request" representing the client's request for the DeleteMLModel operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteMLModel for more information on using the DeleteMLModel API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteMLModelRequest method. req, resp := client.DeleteMLModelRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteMLModelWithContext

func (c *MachineLearning) DeleteMLModelWithContext(ctx aws.Context, input *DeleteMLModelInput, opts ...request.Option) (*DeleteMLModelOutput, error)

DeleteMLModelWithContext is the same as DeleteMLModel with the addition of the ability to pass a context and additional request options.

See DeleteMLModel for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteRealtimeEndpoint

func (c *MachineLearning) DeleteRealtimeEndpoint(input *DeleteRealtimeEndpointInput) (*DeleteRealtimeEndpointOutput, error)

DeleteRealtimeEndpoint API operation for Amazon Machine Learning.

Deletes a real time endpoint of an MLModel.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteRealtimeEndpoint for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteRealtimeEndpointRequest

func (c *MachineLearning) DeleteRealtimeEndpointRequest(input *DeleteRealtimeEndpointInput) (req *request.Request, output *DeleteRealtimeEndpointOutput)

DeleteRealtimeEndpointRequest generates a "aws/request.Request" representing the client's request for the DeleteRealtimeEndpoint operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteRealtimeEndpoint for more information on using the DeleteRealtimeEndpoint API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteRealtimeEndpointRequest method. req, resp := client.DeleteRealtimeEndpointRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteRealtimeEndpointWithContext

func (c *MachineLearning) DeleteRealtimeEndpointWithContext(ctx aws.Context, input *DeleteRealtimeEndpointInput, opts ...request.Option) (*DeleteRealtimeEndpointOutput, error)

DeleteRealtimeEndpointWithContext is the same as DeleteRealtimeEndpoint with the addition of the ability to pass a context and additional request options.

See DeleteRealtimeEndpoint for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DeleteTags

func (c *MachineLearning) DeleteTags(input *DeleteTagsInput) (*DeleteTagsOutput, error)

DeleteTags API operation for Amazon Machine Learning.

Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags.

If you specify a tag that doesn't exist, Amazon ML ignores it.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DeleteTags for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInvalidTagException "InvalidTagException"

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DeleteTagsRequest

func (c *MachineLearning) DeleteTagsRequest(input *DeleteTagsInput) (req *request.Request, output *DeleteTagsOutput)

DeleteTagsRequest generates a "aws/request.Request" representing the client's request for the DeleteTags operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DeleteTags for more information on using the DeleteTags API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DeleteTagsRequest method. req, resp := client.DeleteTagsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DeleteTagsWithContext

func (c *MachineLearning) DeleteTagsWithContext(ctx aws.Context, input *DeleteTagsInput, opts ...request.Option) (*DeleteTagsOutput, error)

DeleteTagsWithContext is the same as DeleteTags with the addition of the ability to pass a context and additional request options.

See DeleteTags for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeBatchPredictions

func (c *MachineLearning) DescribeBatchPredictions(input *DescribeBatchPredictionsInput) (*DescribeBatchPredictionsOutput, error)

DescribeBatchPredictions API operation for Amazon Machine Learning.

Returns a list of BatchPrediction operations that match the search criteria in the request.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DescribeBatchPredictions for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DescribeBatchPredictionsPages

func (c *MachineLearning) DescribeBatchPredictionsPages(input *DescribeBatchPredictionsInput, fn func(*DescribeBatchPredictionsOutput, bool) bool) error

DescribeBatchPredictionsPages iterates over the pages of a DescribeBatchPredictions operation, calling the "fn" function with the response data for each page. To stop iterating, return false from the fn function.

See DescribeBatchPredictions method for more information on how to use this operation.

Note: This operation can generate multiple requests to a service.

// Example iterating over at most 3 pages of a DescribeBatchPredictions operation. pageNum := 0 err := client.DescribeBatchPredictionsPages(params, func(page *DescribeBatchPredictionsOutput, lastPage bool) bool { pageNum++ fmt.Println(page) return pageNum <= 3 })

See Also

For more information about using this API, see AWS API Documentation.

DescribeBatchPredictionsPagesWithContext

func (c *MachineLearning) DescribeBatchPredictionsPagesWithContext(ctx aws.Context, input *DescribeBatchPredictionsInput, fn func(*DescribeBatchPredictionsOutput, bool) bool, opts ...request.Option) error

DescribeBatchPredictionsPagesWithContext same as DescribeBatchPredictionsPages except it takes a Context and allows setting request options on the pages.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeBatchPredictionsRequest

func (c *MachineLearning) DescribeBatchPredictionsRequest(input *DescribeBatchPredictionsInput) (req *request.Request, output *DescribeBatchPredictionsOutput)

DescribeBatchPredictionsRequest generates a "aws/request.Request" representing the client's request for the DescribeBatchPredictions operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DescribeBatchPredictions for more information on using the DescribeBatchPredictions API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DescribeBatchPredictionsRequest method. req, resp := client.DescribeBatchPredictionsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DescribeBatchPredictionsWithContext

func (c *MachineLearning) DescribeBatchPredictionsWithContext(ctx aws.Context, input *DescribeBatchPredictionsInput, opts ...request.Option) (*DescribeBatchPredictionsOutput, error)

DescribeBatchPredictionsWithContext is the same as DescribeBatchPredictions with the addition of the ability to pass a context and additional request options.

See DescribeBatchPredictions for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeDataSources

func (c *MachineLearning) DescribeDataSources(input *DescribeDataSourcesInput) (*DescribeDataSourcesOutput, error)

DescribeDataSources API operation for Amazon Machine Learning.

Returns a list of DataSource that match the search criteria in the request.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DescribeDataSources for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DescribeDataSourcesPages

func (c *MachineLearning) DescribeDataSourcesPages(input *DescribeDataSourcesInput, fn func(*DescribeDataSourcesOutput, bool) bool) error

DescribeDataSourcesPages iterates over the pages of a DescribeDataSources operation, calling the "fn" function with the response data for each page. To stop iterating, return false from the fn function.

See DescribeDataSources method for more information on how to use this operation.

Note: This operation can generate multiple requests to a service.

// Example iterating over at most 3 pages of a DescribeDataSources operation. pageNum := 0 err := client.DescribeDataSourcesPages(params, func(page *DescribeDataSourcesOutput, lastPage bool) bool { pageNum++ fmt.Println(page) return pageNum <= 3 })

See Also

For more information about using this API, see AWS API Documentation.

DescribeDataSourcesPagesWithContext

func (c *MachineLearning) DescribeDataSourcesPagesWithContext(ctx aws.Context, input *DescribeDataSourcesInput, fn func(*DescribeDataSourcesOutput, bool) bool, opts ...request.Option) error

DescribeDataSourcesPagesWithContext same as DescribeDataSourcesPages except it takes a Context and allows setting request options on the pages.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeDataSourcesRequest

func (c *MachineLearning) DescribeDataSourcesRequest(input *DescribeDataSourcesInput) (req *request.Request, output *DescribeDataSourcesOutput)

DescribeDataSourcesRequest generates a "aws/request.Request" representing the client's request for the DescribeDataSources operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DescribeDataSources for more information on using the DescribeDataSources API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DescribeDataSourcesRequest method. req, resp := client.DescribeDataSourcesRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DescribeDataSourcesWithContext

func (c *MachineLearning) DescribeDataSourcesWithContext(ctx aws.Context, input *DescribeDataSourcesInput, opts ...request.Option) (*DescribeDataSourcesOutput, error)

DescribeDataSourcesWithContext is the same as DescribeDataSources with the addition of the ability to pass a context and additional request options.

See DescribeDataSources for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeEvaluations

func (c *MachineLearning) DescribeEvaluations(input *DescribeEvaluationsInput) (*DescribeEvaluationsOutput, error)

DescribeEvaluations API operation for Amazon Machine Learning.

Returns a list of DescribeEvaluations that match the search criteria in the request.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DescribeEvaluations for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DescribeEvaluationsPages

func (c *MachineLearning) DescribeEvaluationsPages(input *DescribeEvaluationsInput, fn func(*DescribeEvaluationsOutput, bool) bool) error

DescribeEvaluationsPages iterates over the pages of a DescribeEvaluations operation, calling the "fn" function with the response data for each page. To stop iterating, return false from the fn function.

See DescribeEvaluations method for more information on how to use this operation.

Note: This operation can generate multiple requests to a service.

// Example iterating over at most 3 pages of a DescribeEvaluations operation. pageNum := 0 err := client.DescribeEvaluationsPages(params, func(page *DescribeEvaluationsOutput, lastPage bool) bool { pageNum++ fmt.Println(page) return pageNum <= 3 })

See Also

For more information about using this API, see AWS API Documentation.

DescribeEvaluationsPagesWithContext

func (c *MachineLearning) DescribeEvaluationsPagesWithContext(ctx aws.Context, input *DescribeEvaluationsInput, fn func(*DescribeEvaluationsOutput, bool) bool, opts ...request.Option) error

DescribeEvaluationsPagesWithContext same as DescribeEvaluationsPages except it takes a Context and allows setting request options on the pages.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeEvaluationsRequest

func (c *MachineLearning) DescribeEvaluationsRequest(input *DescribeEvaluationsInput) (req *request.Request, output *DescribeEvaluationsOutput)

DescribeEvaluationsRequest generates a "aws/request.Request" representing the client's request for the DescribeEvaluations operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DescribeEvaluations for more information on using the DescribeEvaluations API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DescribeEvaluationsRequest method. req, resp := client.DescribeEvaluationsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DescribeEvaluationsWithContext

func (c *MachineLearning) DescribeEvaluationsWithContext(ctx aws.Context, input *DescribeEvaluationsInput, opts ...request.Option) (*DescribeEvaluationsOutput, error)

DescribeEvaluationsWithContext is the same as DescribeEvaluations with the addition of the ability to pass a context and additional request options.

See DescribeEvaluations for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeMLModels

func (c *MachineLearning) DescribeMLModels(input *DescribeMLModelsInput) (*DescribeMLModelsOutput, error)

DescribeMLModels API operation for Amazon Machine Learning.

Returns a list of MLModel that match the search criteria in the request.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DescribeMLModels for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DescribeMLModelsPages

func (c *MachineLearning) DescribeMLModelsPages(input *DescribeMLModelsInput, fn func(*DescribeMLModelsOutput, bool) bool) error

DescribeMLModelsPages iterates over the pages of a DescribeMLModels operation, calling the "fn" function with the response data for each page. To stop iterating, return false from the fn function.

See DescribeMLModels method for more information on how to use this operation.

Note: This operation can generate multiple requests to a service.

// Example iterating over at most 3 pages of a DescribeMLModels operation. pageNum := 0 err := client.DescribeMLModelsPages(params, func(page *DescribeMLModelsOutput, lastPage bool) bool { pageNum++ fmt.Println(page) return pageNum <= 3 })

See Also

For more information about using this API, see AWS API Documentation.

DescribeMLModelsPagesWithContext

func (c *MachineLearning) DescribeMLModelsPagesWithContext(ctx aws.Context, input *DescribeMLModelsInput, fn func(*DescribeMLModelsOutput, bool) bool, opts ...request.Option) error

DescribeMLModelsPagesWithContext same as DescribeMLModelsPages except it takes a Context and allows setting request options on the pages.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeMLModelsRequest

func (c *MachineLearning) DescribeMLModelsRequest(input *DescribeMLModelsInput) (req *request.Request, output *DescribeMLModelsOutput)

DescribeMLModelsRequest generates a "aws/request.Request" representing the client's request for the DescribeMLModels operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DescribeMLModels for more information on using the DescribeMLModels API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DescribeMLModelsRequest method. req, resp := client.DescribeMLModelsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DescribeMLModelsWithContext

func (c *MachineLearning) DescribeMLModelsWithContext(ctx aws.Context, input *DescribeMLModelsInput, opts ...request.Option) (*DescribeMLModelsOutput, error)

DescribeMLModelsWithContext is the same as DescribeMLModels with the addition of the ability to pass a context and additional request options.

See DescribeMLModels for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

DescribeTags

func (c *MachineLearning) DescribeTags(input *DescribeTagsInput) (*DescribeTagsOutput, error)

DescribeTags API operation for Amazon Machine Learning.

Describes one or more of the tags for your Amazon ML object.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation DescribeTags for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

DescribeTagsRequest

func (c *MachineLearning) DescribeTagsRequest(input *DescribeTagsInput) (req *request.Request, output *DescribeTagsOutput)

DescribeTagsRequest generates a "aws/request.Request" representing the client's request for the DescribeTags operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See DescribeTags for more information on using the DescribeTags API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the DescribeTagsRequest method. req, resp := client.DescribeTagsRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

DescribeTagsWithContext

func (c *MachineLearning) DescribeTagsWithContext(ctx aws.Context, input *DescribeTagsInput, opts ...request.Option) (*DescribeTagsOutput, error)

DescribeTagsWithContext is the same as DescribeTags with the addition of the ability to pass a context and additional request options.

See DescribeTags for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

GetBatchPrediction

func (c *MachineLearning) GetBatchPrediction(input *GetBatchPredictionInput) (*GetBatchPredictionOutput, error)

GetBatchPrediction API operation for Amazon Machine Learning.

Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation GetBatchPrediction for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

GetBatchPredictionRequest

func (c *MachineLearning) GetBatchPredictionRequest(input *GetBatchPredictionInput) (req *request.Request, output *GetBatchPredictionOutput)

GetBatchPredictionRequest generates a "aws/request.Request" representing the client's request for the GetBatchPrediction operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See GetBatchPrediction for more information on using the GetBatchPrediction API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the GetBatchPredictionRequest method. req, resp := client.GetBatchPredictionRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

GetBatchPredictionWithContext

func (c *MachineLearning) GetBatchPredictionWithContext(ctx aws.Context, input *GetBatchPredictionInput, opts ...request.Option) (*GetBatchPredictionOutput, error)

GetBatchPredictionWithContext is the same as GetBatchPrediction with the addition of the ability to pass a context and additional request options.

See GetBatchPrediction for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

GetDataSource

func (c *MachineLearning) GetDataSource(input *GetDataSourceInput) (*GetDataSourceOutput, error)

GetDataSource API operation for Amazon Machine Learning.

Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource.

GetDataSource provides results in normal or verbose format. The verbose format adds the schema description and the list of files pointed to by the DataSource to the normal format.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation GetDataSource for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

GetDataSourceRequest

func (c *MachineLearning) GetDataSourceRequest(input *GetDataSourceInput) (req *request.Request, output *GetDataSourceOutput)

GetDataSourceRequest generates a "aws/request.Request" representing the client's request for the GetDataSource operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See GetDataSource for more information on using the GetDataSource API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the GetDataSourceRequest method. req, resp := client.GetDataSourceRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

GetDataSourceWithContext

func (c *MachineLearning) GetDataSourceWithContext(ctx aws.Context, input *GetDataSourceInput, opts ...request.Option) (*GetDataSourceOutput, error)

GetDataSourceWithContext is the same as GetDataSource with the addition of the ability to pass a context and additional request options.

See GetDataSource for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

GetEvaluation

func (c *MachineLearning) GetEvaluation(input *GetEvaluationInput) (*GetEvaluationOutput, error)

GetEvaluation API operation for Amazon Machine Learning.

Returns an Evaluation that includes metadata as well as the current status of the Evaluation.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation GetEvaluation for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

GetEvaluationRequest

func (c *MachineLearning) GetEvaluationRequest(input *GetEvaluationInput) (req *request.Request, output *GetEvaluationOutput)

GetEvaluationRequest generates a "aws/request.Request" representing the client's request for the GetEvaluation operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See GetEvaluation for more information on using the GetEvaluation API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the GetEvaluationRequest method. req, resp := client.GetEvaluationRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

GetEvaluationWithContext

func (c *MachineLearning) GetEvaluationWithContext(ctx aws.Context, input *GetEvaluationInput, opts ...request.Option) (*GetEvaluationOutput, error)

GetEvaluationWithContext is the same as GetEvaluation with the addition of the ability to pass a context and additional request options.

See GetEvaluation for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

GetMLModel

func (c *MachineLearning) GetMLModel(input *GetMLModelInput) (*GetMLModelOutput, error)

GetMLModel API operation for Amazon Machine Learning.

Returns an MLModel that includes detailed metadata, data source information, and the current status of the MLModel.

GetMLModel provides results in normal or verbose format.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation GetMLModel for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

GetMLModelRequest

func (c *MachineLearning) GetMLModelRequest(input *GetMLModelInput) (req *request.Request, output *GetMLModelOutput)

GetMLModelRequest generates a "aws/request.Request" representing the client's request for the GetMLModel operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See GetMLModel for more information on using the GetMLModel API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the GetMLModelRequest method. req, resp := client.GetMLModelRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

GetMLModelWithContext

func (c *MachineLearning) GetMLModelWithContext(ctx aws.Context, input *GetMLModelInput, opts ...request.Option) (*GetMLModelOutput, error)

GetMLModelWithContext is the same as GetMLModel with the addition of the ability to pass a context and additional request options.

See GetMLModel for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

Predict

func (c *MachineLearning) Predict(input *PredictInput) (*PredictOutput, error)

Predict API operation for Amazon Machine Learning.

Generates a prediction for the observation using the specified ML Model.

NoteNot all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation Predict for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeLimitExceededException "LimitExceededException" The subscriber exceeded the maximum number of operations. This exception can occur when listing objects such as DataSource.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

  • ErrCodePredictorNotMountedException "PredictorNotMountedException" The exception is thrown when a predict request is made to an unmounted MLModel.

See Also

For more information about using this API, see AWS API Documentation.

PredictRequest

func (c *MachineLearning) PredictRequest(input *PredictInput) (req *request.Request, output *PredictOutput)

PredictRequest generates a "aws/request.Request" representing the client's request for the Predict operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See Predict for more information on using the Predict API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the PredictRequest method. req, resp := client.PredictRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

PredictWithContext

func (c *MachineLearning) PredictWithContext(ctx aws.Context, input *PredictInput, opts ...request.Option) (*PredictOutput, error)

PredictWithContext is the same as Predict with the addition of the ability to pass a context and additional request options.

See Predict for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

UpdateBatchPrediction

func (c *MachineLearning) UpdateBatchPrediction(input *UpdateBatchPredictionInput) (*UpdateBatchPredictionOutput, error)

UpdateBatchPrediction API operation for Amazon Machine Learning.

Updates the BatchPredictionName of a BatchPrediction.

You can use the GetBatchPrediction operation to view the contents of the updated data element.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation UpdateBatchPrediction for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

UpdateBatchPredictionRequest

func (c *MachineLearning) UpdateBatchPredictionRequest(input *UpdateBatchPredictionInput) (req *request.Request, output *UpdateBatchPredictionOutput)

UpdateBatchPredictionRequest generates a "aws/request.Request" representing the client's request for the UpdateBatchPrediction operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See UpdateBatchPrediction for more information on using the UpdateBatchPrediction API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the UpdateBatchPredictionRequest method. req, resp := client.UpdateBatchPredictionRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

UpdateBatchPredictionWithContext

func (c *MachineLearning) UpdateBatchPredictionWithContext(ctx aws.Context, input *UpdateBatchPredictionInput, opts ...request.Option) (*UpdateBatchPredictionOutput, error)

UpdateBatchPredictionWithContext is the same as UpdateBatchPrediction with the addition of the ability to pass a context and additional request options.

See UpdateBatchPrediction for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

UpdateDataSource

func (c *MachineLearning) UpdateDataSource(input *UpdateDataSourceInput) (*UpdateDataSourceOutput, error)

UpdateDataSource API operation for Amazon Machine Learning.

Updates the DataSourceName of a DataSource.

You can use the GetDataSource operation to view the contents of the updated data element.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation UpdateDataSource for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

UpdateDataSourceRequest

func (c *MachineLearning) UpdateDataSourceRequest(input *UpdateDataSourceInput) (req *request.Request, output *UpdateDataSourceOutput)

UpdateDataSourceRequest generates a "aws/request.Request" representing the client's request for the UpdateDataSource operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See UpdateDataSource for more information on using the UpdateDataSource API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the UpdateDataSourceRequest method. req, resp := client.UpdateDataSourceRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

UpdateDataSourceWithContext

func (c *MachineLearning) UpdateDataSourceWithContext(ctx aws.Context, input *UpdateDataSourceInput, opts ...request.Option) (*UpdateDataSourceOutput, error)

UpdateDataSourceWithContext is the same as UpdateDataSource with the addition of the ability to pass a context and additional request options.

See UpdateDataSource for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

UpdateEvaluation

func (c *MachineLearning) UpdateEvaluation(input *UpdateEvaluationInput) (*UpdateEvaluationOutput, error)

UpdateEvaluation API operation for Amazon Machine Learning.

Updates the EvaluationName of an Evaluation.

You can use the GetEvaluation operation to view the contents of the updated data element.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation UpdateEvaluation for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

UpdateEvaluationRequest

func (c *MachineLearning) UpdateEvaluationRequest(input *UpdateEvaluationInput) (req *request.Request, output *UpdateEvaluationOutput)

UpdateEvaluationRequest generates a "aws/request.Request" representing the client's request for the UpdateEvaluation operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See UpdateEvaluation for more information on using the UpdateEvaluation API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the UpdateEvaluationRequest method. req, resp := client.UpdateEvaluationRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

UpdateEvaluationWithContext

func (c *MachineLearning) UpdateEvaluationWithContext(ctx aws.Context, input *UpdateEvaluationInput, opts ...request.Option) (*UpdateEvaluationOutput, error)

UpdateEvaluationWithContext is the same as UpdateEvaluation with the addition of the ability to pass a context and additional request options.

See UpdateEvaluation for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

UpdateMLModel

func (c *MachineLearning) UpdateMLModel(input *UpdateMLModelInput) (*UpdateMLModelOutput, error)

UpdateMLModel API operation for Amazon Machine Learning.

Updates the MLModelName and the ScoreThreshold of an MLModel.

You can use the GetMLModel operation to view the contents of the updated data element.

Returns awserr.Error for service API and SDK errors. Use runtime type assertions with awserr.Error's Code and Message methods to get detailed information about the error.

See the AWS API reference guide for Amazon Machine Learning's API operation UpdateMLModel for usage and error information.

Returned Error Codes:

  • ErrCodeInvalidInputException "InvalidInputException" An error on the client occurred. Typically, the cause is an invalid input value.

  • ErrCodeResourceNotFoundException "ResourceNotFoundException" A specified resource cannot be located.

  • ErrCodeInternalServerException "InternalServerException" An error on the server occurred when trying to process a request.

See Also

For more information about using this API, see AWS API Documentation.

UpdateMLModelRequest

func (c *MachineLearning) UpdateMLModelRequest(input *UpdateMLModelInput) (req *request.Request, output *UpdateMLModelOutput)

UpdateMLModelRequest generates a "aws/request.Request" representing the client's request for the UpdateMLModel operation. The "output" return value will be populated with the request's response once the request completes successfully.

Use "Send" method on the returned Request to send the API call to the service. the "output" return value is not valid until after Send returns without error.

See UpdateMLModel for more information on using the UpdateMLModel API call, and error handling.

This method is useful when you want to inject custom logic or configuration into the SDK's request lifecycle. Such as custom headers, or retry logic.

// Example sending a request using the UpdateMLModelRequest method. req, resp := client.UpdateMLModelRequest(params) err := req.Send() if err == nil { // resp is now filled fmt.Println(resp) }

See Also

For more information about using this API, see AWS API Documentation.

UpdateMLModelWithContext

func (c *MachineLearning) UpdateMLModelWithContext(ctx aws.Context, input *UpdateMLModelInput, opts ...request.Option) (*UpdateMLModelOutput, error)

UpdateMLModelWithContext is the same as UpdateMLModel with the addition of the ability to pass a context and additional request options.

See UpdateMLModel for details on how to use this API operation.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

See Also

For more information about using this API, see AWS API Documentation.

WaitUntilBatchPredictionAvailable

func (c *MachineLearning) WaitUntilBatchPredictionAvailable(input *DescribeBatchPredictionsInput) error

WaitUntilBatchPredictionAvailable uses the Amazon Machine Learning API operation DescribeBatchPredictions to wait for a condition to be met before returning. If the condition is not met within the max attempt window, an error will be returned.

WaitUntilBatchPredictionAvailableWithContext

func (c *MachineLearning) WaitUntilBatchPredictionAvailableWithContext(ctx aws.Context, input *DescribeBatchPredictionsInput, opts ...request.WaiterOption) error

WaitUntilBatchPredictionAvailableWithContext is an extended version of WaitUntilBatchPredictionAvailable. With the support for passing in a context and options to configure the Waiter and the underlying request options.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

WaitUntilDataSourceAvailable

func (c *MachineLearning) WaitUntilDataSourceAvailable(input *DescribeDataSourcesInput) error

WaitUntilDataSourceAvailable uses the Amazon Machine Learning API operation DescribeDataSources to wait for a condition to be met before returning. If the condition is not met within the max attempt window, an error will be returned.

WaitUntilDataSourceAvailableWithContext

func (c *MachineLearning) WaitUntilDataSourceAvailableWithContext(ctx aws.Context, input *DescribeDataSourcesInput, opts ...request.WaiterOption) error

WaitUntilDataSourceAvailableWithContext is an extended version of WaitUntilDataSourceAvailable. With the support for passing in a context and options to configure the Waiter and the underlying request options.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

WaitUntilEvaluationAvailable

func (c *MachineLearning) WaitUntilEvaluationAvailable(input *DescribeEvaluationsInput) error

WaitUntilEvaluationAvailable uses the Amazon Machine Learning API operation DescribeEvaluations to wait for a condition to be met before returning. If the condition is not met within the max attempt window, an error will be returned.

WaitUntilEvaluationAvailableWithContext

func (c *MachineLearning) WaitUntilEvaluationAvailableWithContext(ctx aws.Context, input *DescribeEvaluationsInput, opts ...request.WaiterOption) error

WaitUntilEvaluationAvailableWithContext is an extended version of WaitUntilEvaluationAvailable. With the support for passing in a context and options to configure the Waiter and the underlying request options.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

WaitUntilMLModelAvailable

func (c *MachineLearning) WaitUntilMLModelAvailable(input *DescribeMLModelsInput) error

WaitUntilMLModelAvailable uses the Amazon Machine Learning API operation DescribeMLModels to wait for a condition to be met before returning. If the condition is not met within the max attempt window, an error will be returned.

WaitUntilMLModelAvailableWithContext

func (c *MachineLearning) WaitUntilMLModelAvailableWithContext(ctx aws.Context, input *DescribeMLModelsInput, opts ...request.WaiterOption) error

WaitUntilMLModelAvailableWithContext is an extended version of WaitUntilMLModelAvailable. With the support for passing in a context and options to configure the Waiter and the underlying request options.

The context must be non-nil and will be used for request cancellation. If the context is nil a panic will occur. In the future the SDK may create sub-contexts for http.Requests. See https://golang.org/pkg/context/ for more information on using Contexts.

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