Class Evaluation
- All Implemented Interfaces:
Serializable,SdkPojo,ToCopyableBuilder<Evaluation.Builder,Evaluation>
Represents the output of GetEvaluation operation.
The content consists of the detailed metadata and data file information and the current status of the
Evaluation.
- See Also:
-
Nested Class Summary
Nested Classes -
Method Summary
Modifier and TypeMethodDescriptionstatic Evaluation.Builderbuilder()final LongReturns the value of the ComputeTime property for this object.final InstantThe time that theEvaluationwas created.final StringThe AWS user account that invoked the evaluation.final booleanfinal booleanequalsBySdkFields(Object obj) Indicates whether some other object is "equal to" this one by SDK fields.final StringThe ID of theDataSourcethat is used to evaluate theMLModel.final StringThe ID that is assigned to theEvaluationat creation.final InstantReturns the value of the FinishedAt property for this object.final <T> Optional<T> getValueForField(String fieldName, Class<T> clazz) final inthashCode()final StringThe location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.final InstantThe time of the most recent edit to theEvaluation.final Stringmessage()A description of the most recent details about evaluating theMLModel.final StringThe ID of theMLModelthat is the focus of the evaluation.final Stringname()A user-supplied name or description of theEvaluation.final PerformanceMetricsMeasurements of how well theMLModelperformed, using observations referenced by theDataSource.static Class<? extends Evaluation.Builder> final InstantReturns the value of the StartedAt property for this object.final EntityStatusstatus()The status of the evaluation.final StringThe status of the evaluation.Take this object and create a builder that contains all of the current property values of this object.final StringtoString()Returns a string representation of this object.Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
-
Method Details
-
evaluationId
The ID that is assigned to the
Evaluationat creation.- Returns:
- The ID that is assigned to the
Evaluationat creation.
-
mlModelId
The ID of the
MLModelthat is the focus of the evaluation.- Returns:
- The ID of the
MLModelthat is the focus of the evaluation.
-
evaluationDataSourceId
The ID of the
DataSourcethat is used to evaluate theMLModel.- Returns:
- The ID of the
DataSourcethat is used to evaluate theMLModel.
-
inputDataLocationS3
The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
- Returns:
- The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
-
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:
- 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.
-
createdAt
The time that the
Evaluationwas created. The time is expressed in epoch time.- Returns:
- The time that the
Evaluationwas created. 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.- Returns:
- The time of the most recent edit to the
Evaluation. The time is expressed in epoch time.
-
name
A user-supplied name or description of the
Evaluation.- Returns:
- A user-supplied name or description of the
Evaluation.
-
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 anMLModel. -
INPROGRESS- The evaluation is underway. -
FAILED- The request to evaluate anMLModeldid not run to completion. It is not usable. -
COMPLETED- The evaluation process completed successfully. -
DELETED- TheEvaluationis marked as deleted. It is not usable.
If the service returns an enum value that is not available in the current SDK version,
statuswill returnEntityStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromstatusAsString().- Returns:
- 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 anMLModel. -
INPROGRESS- The evaluation is underway. -
FAILED- The request to evaluate anMLModeldid not run to completion. It is not usable. -
COMPLETED- The evaluation process completed successfully. -
DELETED- TheEvaluationis marked as deleted. It is not usable.
-
- See Also:
-
-
statusAsString
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 anMLModel. -
INPROGRESS- The evaluation is underway. -
FAILED- The request to evaluate anMLModeldid not run to completion. It is not usable. -
COMPLETED- The evaluation process completed successfully. -
DELETED- TheEvaluationis marked as deleted. It is not usable.
If the service returns an enum value that is not available in the current SDK version,
statuswill returnEntityStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available fromstatusAsString().- Returns:
- 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 anMLModel. -
INPROGRESS- The evaluation is underway. -
FAILED- The request to evaluate anMLModeldid not run to completion. It is not usable. -
COMPLETED- The evaluation process completed successfully. -
DELETED- TheEvaluationis marked as deleted. It is not usable.
-
- See Also:
-
-
performanceMetrics
Measurements of how well the
MLModelperformed, using observations referenced by theDataSource. One of the following metrics is returned, based on the type of theMLModel:-
BinaryAUC: A binary
MLModeluses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: A regression
MLModeluses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. -
MulticlassAvgFScore: A multiclass
MLModeluses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
- Returns:
- Measurements of how well the
MLModelperformed, using observations referenced by theDataSource. One of the following metrics is returned, based on the type of theMLModel:-
BinaryAUC: A binary
MLModeluses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: A regression
MLModeluses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. -
MulticlassAvgFScore: A multiclass
MLModeluses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
-
-
-
message
A description of the most recent details about evaluating the
MLModel.- Returns:
- A description of the most recent details about evaluating the
MLModel.
-
computeTime
Returns the value of the ComputeTime property for this object.- Returns:
- The value of the ComputeTime property for this object.
-
finishedAt
Returns the value of the FinishedAt property for this object.- Returns:
- The value of the FinishedAt property for this object.
-
startedAt
Returns the value of the StartedAt property for this object.- Returns:
- The value of the StartedAt property for this object.
-
toBuilder
Description copied from interface:ToCopyableBuilderTake this object and create a builder that contains all of the current property values of this object.- Specified by:
toBuilderin interfaceToCopyableBuilder<Evaluation.Builder,Evaluation> - Returns:
- a builder for type T
-
builder
-
serializableBuilderClass
-
hashCode
-
equals
-
equalsBySdkFields
Description copied from interface:SdkPojoIndicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in anSdkPojoclass, and is generated based on a service model.If an
SdkPojoclass does not have any inherited fields,equalsBySdkFieldsandequalsare essentially the same.- Specified by:
equalsBySdkFieldsin interfaceSdkPojo- Parameters:
obj- the object to be compared with- Returns:
- true if the other object equals to this object by sdk fields, false otherwise.
-
toString
-
getValueForField
-
sdkFields
-