Package software.amazon.awssdk.services.machinelearning.model

Interface Evaluation.Builder

All Superinterfaces:

CopyableBuilder<Evaluation.Builder,Evaluation>, SdkBuilder<Evaluation.Builder,Evaluation>

Enclosing class:

Evaluation

public static interface Evaluation.Builder
extends CopyableBuilder<Evaluation.Builder,Evaluation>

Method Summary

Modifier and Type	Method	Description
Evaluation.Builder	computeTime(Long computeTime)
Evaluation.Builder	createdAt(Date createdAt)	The time that the Evaluation was created.
Evaluation.Builder	createdByIamUser(String createdByIamUser)	The AWS user account that invoked the evaluation.
Evaluation.Builder	evaluationDataSourceId(String evaluationDataSourceId)	The ID of the DataSource that is used to evaluate the MLModel.
Evaluation.Builder	evaluationId(String evaluationId)	The ID that is assigned to the Evaluation at creation.
Evaluation.Builder	finishedAt(Date finishedAt)
Evaluation.Builder	inputDataLocationS3(String inputDataLocationS3)	The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
Evaluation.Builder	lastUpdatedAt(Date lastUpdatedAt)	The time of the most recent edit to the Evaluation.
Evaluation.Builder	message(String message)	A description of the most recent details about evaluating the MLModel.
Evaluation.Builder	mlModelId(String mlModelId)	The ID of the MLModel that is the focus of the evaluation.
Evaluation.Builder	name(String name)	A user-supplied name or description of the Evaluation.
Evaluation.Builder	performanceMetrics(PerformanceMetrics performanceMetrics)	Measurements of how well the MLModel performed, using observations referenced by the DataSource.
Evaluation.Builder	startedAt(Date startedAt)
Evaluation.Builder	status(String status)	The status of the evaluation.
Evaluation.Builder	status(EntityStatus status)	The status of the evaluation.

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

apply, build

Method Detail

evaluationId

Evaluation.Builder evaluationId(String evaluationId)

The ID that is assigned to the Evaluation at creation.

Parameters:

evaluationId - The ID that is assigned to the Evaluation at creation.

Returns:

Returns a reference to this object so that method calls can be chained together.

mlModelId

Evaluation.Builder mlModelId(String mlModelId)

The ID of the MLModel that is the focus of the evaluation.

Parameters:

mlModelId - The ID of the MLModel that is the focus of the evaluation.

Returns:

Returns a reference to this object so that method calls can be chained together.

evaluationDataSourceId

Evaluation.Builder evaluationDataSourceId(String evaluationDataSourceId)

The ID of the DataSource that is used to evaluate the MLModel.

Parameters:

evaluationDataSourceId - The ID of the DataSource that is used to evaluate the MLModel.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataLocationS3

Evaluation.Builder inputDataLocationS3(String inputDataLocationS3)

The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.

Parameters:

inputDataLocationS3 - The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.

Returns:

Returns a reference to this object so that method calls can be chained together.

createdByIamUser

Evaluation.Builder createdByIamUser(String createdByIamUser)

The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Parameters:

createdByIamUser - The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

Returns:

Returns a reference to this object so that method calls can be chained together.

createdAt

Evaluation.Builder createdAt(Date createdAt)

The time that the Evaluation was created. The time is expressed in epoch time.

Parameters:

createdAt - The time that the Evaluation was created. The time is expressed in epoch time.

Returns:

Returns a reference to this object so that method calls can be chained together.

lastUpdatedAt

Evaluation.Builder lastUpdatedAt(Date lastUpdatedAt)

The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

Parameters:

lastUpdatedAt - The time of the most recent edit to the Evaluation. The time is expressed in epoch time.

Returns:

Returns a reference to this object so that method calls can be chained together.

name

Evaluation.Builder name(String name)

A user-supplied name or description of the Evaluation.

Parameters:

name - A user-supplied name or description of the Evaluation.

Returns:

Returns a reference to this object so that method calls can be chained together.

status

Evaluation.Builder status(String status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

EntityStatus

status

Evaluation.Builder status(EntityStatus status)

The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Parameters:

status - The status of the evaluation. This element can have one of the following values:

• PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an MLModel.
• INPROGRESS - The evaluation is underway.
• FAILED - The request to evaluate an MLModel did not run to completion. It is not usable.
• COMPLETED - The evaluation process completed successfully.
• DELETED - The Evaluation is marked as deleted. It is not usable.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

EntityStatus

performanceMetrics

Evaluation.Builder performanceMetrics(PerformanceMetrics performanceMetrics)

Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics is returned, based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Parameters:

performanceMetrics - Measurements of how well the MLModel performed, using observations referenced by the DataSource. One of the following metrics is returned, based on the type of the MLModel:

• BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

• RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

• MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

Returns:

Returns a reference to this object so that method calls can be chained together.

message

Evaluation.Builder message(String message)

A description of the most recent details about evaluating the MLModel.

Parameters:

message - A description of the most recent details about evaluating the MLModel.

Returns:

Returns a reference to this object so that method calls can be chained together.

computeTime

Evaluation.Builder computeTime(Long computeTime)

Parameters:

computeTime -

Returns:

Returns a reference to this object so that method calls can be chained together.

finishedAt

Evaluation.Builder finishedAt(Date finishedAt)

Parameters:

finishedAt -

Returns:

Returns a reference to this object so that method calls can be chained together.

startedAt

Evaluation.Builder startedAt(Date startedAt)

Parameters:

startedAt -

Returns:

Returns a reference to this object so that method calls can be chained together.