public static interface Evaluation.Builder extends CopyableBuilder<Evaluation.Builder,Evaluation>
Modifier and Type | Method and Description |
---|---|
Evaluation.Builder |
computeTime(Long computeTime)
Sets the value of the ComputeTime property for this object.
|
Evaluation.Builder |
createdAt(Instant 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(Instant finishedAt)
Sets the value of the FinishedAt property for this object.
|
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(Instant 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 . |
default Evaluation.Builder |
performanceMetrics(Consumer<PerformanceMetrics.Builder> performanceMetrics)
Measurements of how well the
MLModel performed, using observations referenced by the
DataSource . |
Evaluation.Builder |
performanceMetrics(PerformanceMetrics performanceMetrics)
Measurements of how well the
MLModel performed, using observations referenced by the
DataSource . |
Evaluation.Builder |
startedAt(Instant startedAt)
Sets the value of the StartedAt property for this object.
|
Evaluation.Builder |
status(EntityStatus status)
The status of the evaluation.
|
Evaluation.Builder |
status(String status)
The status of the evaluation.
|
copy
applyMutation, build
Evaluation.Builder evaluationId(String evaluationId)
The ID that is assigned to the Evaluation
at creation.
evaluationId
- The ID that is assigned to the Evaluation
at creation.Evaluation.Builder mlModelId(String mlModelId)
The ID of the MLModel
that is the focus of the evaluation.
mlModelId
- The ID of the MLModel
that is the focus of the evaluation.Evaluation.Builder evaluationDataSourceId(String evaluationDataSourceId)
The ID of the DataSource
that is used to evaluate the MLModel
.
evaluationDataSourceId
- The ID of the DataSource
that is used to evaluate the MLModel
.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.
inputDataLocationS3
- The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the
evaluation.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.
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.Evaluation.Builder createdAt(Instant createdAt)
The time that the Evaluation
was created. The time is expressed in epoch time.
createdAt
- The time that the Evaluation
was created. The time is expressed in epoch time.Evaluation.Builder lastUpdatedAt(Instant lastUpdatedAt)
The time of the most recent edit to the Evaluation
. The time is expressed in epoch time.
lastUpdatedAt
- The time of the most recent edit to the Evaluation
. The time is expressed in epoch time.Evaluation.Builder name(String name)
A user-supplied name or description of the Evaluation
.
name
- A user-supplied name or description of the Evaluation
.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.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.EntityStatus
,
EntityStatus
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.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.EntityStatus
,
EntityStatus
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.
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.
default Evaluation.Builder performanceMetrics(Consumer<PerformanceMetrics.Builder> 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.
This is a convenience that creates an instance of thePerformanceMetrics.Builder
avoiding the need to
create one manually via PerformanceMetrics.builder()
.
When the Consumer
completes, SdkBuilder.build()
is called immediately and its
result is passed to performanceMetrics(PerformanceMetrics)
.performanceMetrics
- a consumer that will call methods on PerformanceMetrics.Builder
performanceMetrics(PerformanceMetrics)
Evaluation.Builder message(String message)
A description of the most recent details about evaluating the MLModel
.
message
- A description of the most recent details about evaluating the MLModel
.Evaluation.Builder computeTime(Long computeTime)
computeTime
- The new value for the ComputeTime property for this object.Evaluation.Builder finishedAt(Instant finishedAt)
finishedAt
- The new value for the FinishedAt property for this object.Evaluation.Builder startedAt(Instant startedAt)
startedAt
- The new value for the StartedAt property for this object.Copyright © 2017 Amazon Web Services, Inc. All Rights Reserved.