public class GetEvaluationResult extends Object implements Serializable, Cloneable
Represents the output of a GetEvaluation operation and describes an
Evaluation
.
Constructor and Description |
---|
GetEvaluationResult() |
Modifier and Type | Method and Description |
---|---|
GetEvaluationResult |
clone() |
boolean |
equals(Object obj) |
Date |
getCreatedAt()
The time that the
Evaluation was created. |
String |
getCreatedByIamUser()
The AWS user account that invoked the evaluation.
|
String |
getEvaluationDataSourceId()
The
DataSource used for this evaluation. |
String |
getEvaluationId()
The evaluation ID which is same as the
EvaluationId in the
request. |
String |
getInputDataLocationS3()
The location of the data file or directory in Amazon Simple Storage
Service (Amazon S3).
|
Date |
getLastUpdatedAt()
The time of the most recent edit to the
BatchPrediction . |
String |
getLogUri()
A link to the file that contains logs of the CreateEvaluation
operation.
|
String |
getMessage()
A description of the most recent details about evaluating the
MLModel . |
String |
getMLModelId()
The ID of the
MLModel that was the focus of the evaluation. |
String |
getName()
A user-supplied name or description of the
Evaluation . |
PerformanceMetrics |
getPerformanceMetrics()
Measurements of how well the
MLModel performed using
observations referenced by the DataSource . |
String |
getStatus()
The status of the evaluation.
|
int |
hashCode() |
void |
setCreatedAt(Date createdAt)
The time that the
Evaluation was created. |
void |
setCreatedByIamUser(String createdByIamUser)
The AWS user account that invoked the evaluation.
|
void |
setEvaluationDataSourceId(String evaluationDataSourceId)
The
DataSource used for this evaluation. |
void |
setEvaluationId(String evaluationId)
The evaluation ID which is same as the
EvaluationId in the
request. |
void |
setInputDataLocationS3(String inputDataLocationS3)
The location of the data file or directory in Amazon Simple Storage
Service (Amazon S3).
|
void |
setLastUpdatedAt(Date lastUpdatedAt)
The time of the most recent edit to the
BatchPrediction . |
void |
setLogUri(String logUri)
A link to the file that contains logs of the CreateEvaluation
operation.
|
void |
setMessage(String message)
A description of the most recent details about evaluating the
MLModel . |
void |
setMLModelId(String mLModelId)
The ID of the
MLModel that was the focus of the evaluation. |
void |
setName(String name)
A user-supplied name or description of the
Evaluation . |
void |
setPerformanceMetrics(PerformanceMetrics performanceMetrics)
Measurements of how well the
MLModel performed using
observations referenced by the DataSource . |
void |
setStatus(EntityStatus status)
The status of the evaluation.
|
void |
setStatus(String status)
The status of the evaluation.
|
String |
toString()
Returns a string representation of this object; useful for testing and
debugging.
|
GetEvaluationResult |
withCreatedAt(Date createdAt)
The time that the
Evaluation was created. |
GetEvaluationResult |
withCreatedByIamUser(String createdByIamUser)
The AWS user account that invoked the evaluation.
|
GetEvaluationResult |
withEvaluationDataSourceId(String evaluationDataSourceId)
The
DataSource used for this evaluation. |
GetEvaluationResult |
withEvaluationId(String evaluationId)
The evaluation ID which is same as the
EvaluationId in the
request. |
GetEvaluationResult |
withInputDataLocationS3(String inputDataLocationS3)
The location of the data file or directory in Amazon Simple Storage
Service (Amazon S3).
|
GetEvaluationResult |
withLastUpdatedAt(Date lastUpdatedAt)
The time of the most recent edit to the
BatchPrediction . |
GetEvaluationResult |
withLogUri(String logUri)
A link to the file that contains logs of the CreateEvaluation
operation.
|
GetEvaluationResult |
withMessage(String message)
A description of the most recent details about evaluating the
MLModel . |
GetEvaluationResult |
withMLModelId(String mLModelId)
The ID of the
MLModel that was the focus of the evaluation. |
GetEvaluationResult |
withName(String name)
A user-supplied name or description of the
Evaluation . |
GetEvaluationResult |
withPerformanceMetrics(PerformanceMetrics performanceMetrics)
Measurements of how well the
MLModel performed using
observations referenced by the DataSource . |
GetEvaluationResult |
withStatus(EntityStatus status)
The status of the evaluation.
|
GetEvaluationResult |
withStatus(String status)
The status of the evaluation.
|
public void setEvaluationId(String evaluationId)
The evaluation ID which is same as the EvaluationId
in the
request.
evaluationId
- The evaluation ID which is same as the EvaluationId
in the request.public String getEvaluationId()
The evaluation ID which is same as the EvaluationId
in the
request.
EvaluationId
in the request.public GetEvaluationResult withEvaluationId(String evaluationId)
The evaluation ID which is same as the EvaluationId
in the
request.
evaluationId
- The evaluation ID which is same as the EvaluationId
in the request.public void setMLModelId(String mLModelId)
The ID of the MLModel
that was the focus of the evaluation.
mLModelId
- The ID of the MLModel
that was the focus of the
evaluation.public String getMLModelId()
The ID of the MLModel
that was the focus of the evaluation.
MLModel
that was the focus of the
evaluation.public GetEvaluationResult withMLModelId(String mLModelId)
The ID of the MLModel
that was the focus of the evaluation.
mLModelId
- The ID of the MLModel
that was the focus of the
evaluation.public void setEvaluationDataSourceId(String evaluationDataSourceId)
The DataSource
used for this evaluation.
evaluationDataSourceId
- The DataSource
used for this evaluation.public String getEvaluationDataSourceId()
The DataSource
used for this evaluation.
DataSource
used for this evaluation.public GetEvaluationResult withEvaluationDataSourceId(String evaluationDataSourceId)
The DataSource
used for this evaluation.
evaluationDataSourceId
- The DataSource
used for this evaluation.public void setInputDataLocationS3(String inputDataLocationS3)
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
inputDataLocationS3
- The location of the data file or directory in Amazon Simple
Storage Service (Amazon S3).public String getInputDataLocationS3()
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
public GetEvaluationResult withInputDataLocationS3(String inputDataLocationS3)
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
inputDataLocationS3
- The location of the data file or directory in Amazon Simple
Storage Service (Amazon S3).public void setCreatedByIamUser(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.public String getCreatedByIamUser()
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.
public GetEvaluationResult withCreatedByIamUser(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.public void setCreatedAt(Date 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.public Date getCreatedAt()
The time that the Evaluation
was created. The time is
expressed in epoch time.
Evaluation
was created. The time
is expressed in epoch time.public GetEvaluationResult withCreatedAt(Date 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.public void setLastUpdatedAt(Date lastUpdatedAt)
The time of the most recent edit to the BatchPrediction
. The
time is expressed in epoch time.
lastUpdatedAt
- The time of the most recent edit to the
BatchPrediction
. The time is expressed in epoch time.public Date getLastUpdatedAt()
The time of the most recent edit to the BatchPrediction
. The
time is expressed in epoch time.
BatchPrediction
. The time is expressed in epoch
time.public GetEvaluationResult withLastUpdatedAt(Date lastUpdatedAt)
The time of the most recent edit to the BatchPrediction
. The
time is expressed in epoch time.
lastUpdatedAt
- The time of the most recent edit to the
BatchPrediction
. The time is expressed in epoch time.public void setName(String name)
A user-supplied name or description of the Evaluation
.
name
- A user-supplied name or description of the Evaluation
.public String getName()
A user-supplied name or description of the Evaluation
.
Evaluation
.public GetEvaluationResult withName(String name)
A user-supplied name or description of the Evaluation
.
name
- A user-supplied name or description of the Evaluation
.public void setStatus(String status)
The status of the evaluation. This element can have one of the following values:
PENDING
- Amazon Machine Language (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 Language (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
public String getStatus()
The status of the evaluation. This element can have one of the following values:
PENDING
- Amazon Machine Language (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.PENDING
- Amazon Machine Language (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
public GetEvaluationResult withStatus(String status)
The status of the evaluation. This element can have one of the following values:
PENDING
- Amazon Machine Language (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 Language (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
public void setStatus(EntityStatus status)
The status of the evaluation. This element can have one of the following values:
PENDING
- Amazon Machine Language (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 Language (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
public GetEvaluationResult withStatus(EntityStatus status)
The status of the evaluation. This element can have one of the following values:
PENDING
- Amazon Machine Language (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 Language (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
public void setPerformanceMetrics(PerformanceMetrics performanceMetrics)
Measurements of how well the MLModel
performed using
observations referenced by the DataSource
. One of the
following metric 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 metric 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.
public PerformanceMetrics getPerformanceMetrics()
Measurements of how well the MLModel
performed using
observations referenced by the DataSource
. One of the
following metric 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.
MLModel
performed using
observations referenced by the DataSource
. One of
the following metric 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.
public GetEvaluationResult withPerformanceMetrics(PerformanceMetrics performanceMetrics)
Measurements of how well the MLModel
performed using
observations referenced by the DataSource
. One of the
following metric 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 metric 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.
public void setLogUri(String logUri)
A link to the file that contains logs of the CreateEvaluation operation.
logUri
- A link to the file that contains logs of the
CreateEvaluation operation.public String getLogUri()
A link to the file that contains logs of the CreateEvaluation operation.
public GetEvaluationResult withLogUri(String logUri)
A link to the file that contains logs of the CreateEvaluation operation.
logUri
- A link to the file that contains logs of the
CreateEvaluation operation.public void setMessage(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
.public String getMessage()
A description of the most recent details about evaluating the
MLModel
.
MLModel
.public GetEvaluationResult withMessage(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
.public String toString()
toString
in class Object
Object.toString()
public GetEvaluationResult clone()
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