DescribeModelResult (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceResult<ResponseMetadata>
- - com.amazonaws.services.lookoutequipment.model.DescribeModelResult

All Implemented Interfaces:: Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class DescribeModelResult
extends AmazonWebServiceResult<ResponseMetadata>
implements Serializable, Cloneable

See Also:: AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

DescribeModelResult()

Constructors
Constructor and Description
`DescribeModelResult()`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`DescribeModelResult`	`clone()`
`boolean`	`equals(Object obj)`
`Date`	`getAccumulatedInferenceDataEndTime()` Indicates the end time of the inference data that has been accumulated.
`Date`	`getAccumulatedInferenceDataStartTime()` Indicates the start time of the inference data that has been accumulated.
`Long`	`getActiveModelVersion()` The name of the model version used by the inference schedular when running a scheduled inference execution.
`String`	`getActiveModelVersionArn()` The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
`Date`	`getCreatedAt()` Indicates the time and date at which the machine learning model was created.
`DataPreProcessingConfiguration`	`getDataPreProcessingConfiguration()` The configuration is the `TargetSamplingRate`, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment.
`String`	`getDatasetArn()` The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
`String`	`getDatasetName()` The name of the dataset being used by the machine learning being described.
`Date`	`getEvaluationDataEndTime()` Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
`Date`	`getEvaluationDataStartTime()` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
`String`	`getFailedReason()` If the training of the machine learning model failed, this indicates the reason for that failure.
`Date`	`getImportJobEndTime()` The date and time when the import job was completed.
`Date`	`getImportJobStartTime()` The date and time when the import job was started.
`LabelsInputConfiguration`	`getLabelsInputConfiguration()` Specifies configuration information about the labels input, including its S3 location.
`Date`	`getLastUpdatedTime()` Indicates the last time the machine learning model was updated.
`Integer`	`getLatestScheduledRetrainingAvailableDataInDays()` Indicates the number of days of data used in the most recent scheduled retraining run.
`String`	`getLatestScheduledRetrainingFailedReason()` If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
`Long`	`getLatestScheduledRetrainingModelVersion()` Indicates the most recent model version that was generated by retraining.
`Date`	`getLatestScheduledRetrainingStartTime()` Indicates the start time of the most recent scheduled retraining run.
`String`	`getLatestScheduledRetrainingStatus()` Indicates the status of the most recent scheduled retraining run.
`String`	`getModelArn()` The Amazon Resource Name (ARN) of the machine learning model being described.
`ModelDiagnosticsOutputConfiguration`	`getModelDiagnosticsOutputConfiguration()` Configuration information for the model's pointwise model diagnostics.
`String`	`getModelMetrics()` The Model Metrics show an aggregated summary of the model's performance within the evaluation time range.
`String`	`getModelName()` The name of the machine learning model being described.
`String`	`getModelQuality()` Provides a quality assessment for a model that uses labels.
`Date`	`getModelVersionActivatedAt()` The date the active model version was activated.
`Date`	`getNextScheduledRetrainingStartDate()` Indicates the date and time that the next scheduled retraining run will start on.
`String`	`getOffCondition()` Indicates that the asset associated with this sensor has been shut off.
`Long`	`getPreviousActiveModelVersion()` The model version that was set as the active model version prior to the current active model version.
`String`	`getPreviousActiveModelVersionArn()` The ARN of the model version that was set as the active model version prior to the current active model version.
`Date`	`getPreviousModelVersionActivatedAt()` The date and time when the previous active model version was activated.
`String`	`getPriorModelMetrics()` If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range.
`String`	`getRetrainingSchedulerStatus()` Indicates the status of the retraining scheduler.
`String`	`getRoleArn()` The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
`String`	`getSchema()` A JSON description of the data that is in each time series dataset, including names, column names, and data types.
`String`	`getServerSideKmsKeyId()` Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
`String`	`getSourceModelVersionArn()` The Amazon Resource Name (ARN) of the source model version.
`String`	`getStatus()` Specifies the current status of the model being described.
`Date`	`getTrainingDataEndTime()` Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
`Date`	`getTrainingDataStartTime()` Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
`Date`	`getTrainingExecutionEndTime()` Indicates the time at which the training of the machine learning model was completed.
`Date`	`getTrainingExecutionStartTime()` Indicates the time at which the training of the machine learning model began.
`int`	`hashCode()`
`void`	`setAccumulatedInferenceDataEndTime(Date accumulatedInferenceDataEndTime)` Indicates the end time of the inference data that has been accumulated.
`void`	`setAccumulatedInferenceDataStartTime(Date accumulatedInferenceDataStartTime)` Indicates the start time of the inference data that has been accumulated.
`void`	`setActiveModelVersion(Long activeModelVersion)` The name of the model version used by the inference schedular when running a scheduled inference execution.
`void`	`setActiveModelVersionArn(String activeModelVersionArn)` The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
`void`	`setCreatedAt(Date createdAt)` Indicates the time and date at which the machine learning model was created.
`void`	`setDataPreProcessingConfiguration(DataPreProcessingConfiguration dataPreProcessingConfiguration)` The configuration is the `TargetSamplingRate`, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment.
`void`	`setDatasetArn(String datasetArn)` The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
`void`	`setDatasetName(String datasetName)` The name of the dataset being used by the machine learning being described.
`void`	`setEvaluationDataEndTime(Date evaluationDataEndTime)` Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
`void`	`setEvaluationDataStartTime(Date evaluationDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
`void`	`setFailedReason(String failedReason)` If the training of the machine learning model failed, this indicates the reason for that failure.
`void`	`setImportJobEndTime(Date importJobEndTime)` The date and time when the import job was completed.
`void`	`setImportJobStartTime(Date importJobStartTime)` The date and time when the import job was started.
`void`	`setLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)` Specifies configuration information about the labels input, including its S3 location.
`void`	`setLastUpdatedTime(Date lastUpdatedTime)` Indicates the last time the machine learning model was updated.
`void`	`setLatestScheduledRetrainingAvailableDataInDays(Integer latestScheduledRetrainingAvailableDataInDays)` Indicates the number of days of data used in the most recent scheduled retraining run.
`void`	`setLatestScheduledRetrainingFailedReason(String latestScheduledRetrainingFailedReason)` If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
`void`	`setLatestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion)` Indicates the most recent model version that was generated by retraining.
`void`	`setLatestScheduledRetrainingStartTime(Date latestScheduledRetrainingStartTime)` Indicates the start time of the most recent scheduled retraining run.
`void`	`setLatestScheduledRetrainingStatus(String latestScheduledRetrainingStatus)` Indicates the status of the most recent scheduled retraining run.
`void`	`setModelArn(String modelArn)` The Amazon Resource Name (ARN) of the machine learning model being described.
`void`	`setModelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration)` Configuration information for the model's pointwise model diagnostics.
`void`	`setModelMetrics(String modelMetrics)` The Model Metrics show an aggregated summary of the model's performance within the evaluation time range.
`void`	`setModelName(String modelName)` The name of the machine learning model being described.
`void`	`setModelQuality(String modelQuality)` Provides a quality assessment for a model that uses labels.
`void`	`setModelVersionActivatedAt(Date modelVersionActivatedAt)` The date the active model version was activated.
`void`	`setNextScheduledRetrainingStartDate(Date nextScheduledRetrainingStartDate)` Indicates the date and time that the next scheduled retraining run will start on.
`void`	`setOffCondition(String offCondition)` Indicates that the asset associated with this sensor has been shut off.
`void`	`setPreviousActiveModelVersion(Long previousActiveModelVersion)` The model version that was set as the active model version prior to the current active model version.
`void`	`setPreviousActiveModelVersionArn(String previousActiveModelVersionArn)` The ARN of the model version that was set as the active model version prior to the current active model version.
`void`	`setPreviousModelVersionActivatedAt(Date previousModelVersionActivatedAt)` The date and time when the previous active model version was activated.
`void`	`setPriorModelMetrics(String priorModelMetrics)` If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range.
`void`	`setRetrainingSchedulerStatus(String retrainingSchedulerStatus)` Indicates the status of the retraining scheduler.
`void`	`setRoleArn(String roleArn)` The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
`void`	`setSchema(String schema)` A JSON description of the data that is in each time series dataset, including names, column names, and data types.
`void`	`setServerSideKmsKeyId(String serverSideKmsKeyId)` Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
`void`	`setSourceModelVersionArn(String sourceModelVersionArn)` The Amazon Resource Name (ARN) of the source model version.
`void`	`setStatus(String status)` Specifies the current status of the model being described.
`void`	`setTrainingDataEndTime(Date trainingDataEndTime)` Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
`void`	`setTrainingDataStartTime(Date trainingDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
`void`	`setTrainingExecutionEndTime(Date trainingExecutionEndTime)` Indicates the time at which the training of the machine learning model was completed.
`void`	`setTrainingExecutionStartTime(Date trainingExecutionStartTime)` Indicates the time at which the training of the machine learning model began.
`String`	`toString()` Returns a string representation of this object.
`DescribeModelResult`	`withAccumulatedInferenceDataEndTime(Date accumulatedInferenceDataEndTime)` Indicates the end time of the inference data that has been accumulated.
`DescribeModelResult`	`withAccumulatedInferenceDataStartTime(Date accumulatedInferenceDataStartTime)` Indicates the start time of the inference data that has been accumulated.
`DescribeModelResult`	`withActiveModelVersion(Long activeModelVersion)` The name of the model version used by the inference schedular when running a scheduled inference execution.
`DescribeModelResult`	`withActiveModelVersionArn(String activeModelVersionArn)` The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
`DescribeModelResult`	`withCreatedAt(Date createdAt)` Indicates the time and date at which the machine learning model was created.
`DescribeModelResult`	`withDataPreProcessingConfiguration(DataPreProcessingConfiguration dataPreProcessingConfiguration)` The configuration is the `TargetSamplingRate`, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment.
`DescribeModelResult`	`withDatasetArn(String datasetArn)` The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
`DescribeModelResult`	`withDatasetName(String datasetName)` The name of the dataset being used by the machine learning being described.
`DescribeModelResult`	`withEvaluationDataEndTime(Date evaluationDataEndTime)` Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
`DescribeModelResult`	`withEvaluationDataStartTime(Date evaluationDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
`DescribeModelResult`	`withFailedReason(String failedReason)` If the training of the machine learning model failed, this indicates the reason for that failure.
`DescribeModelResult`	`withImportJobEndTime(Date importJobEndTime)` The date and time when the import job was completed.
`DescribeModelResult`	`withImportJobStartTime(Date importJobStartTime)` The date and time when the import job was started.
`DescribeModelResult`	`withLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)` Specifies configuration information about the labels input, including its S3 location.
`DescribeModelResult`	`withLastUpdatedTime(Date lastUpdatedTime)` Indicates the last time the machine learning model was updated.
`DescribeModelResult`	`withLatestScheduledRetrainingAvailableDataInDays(Integer latestScheduledRetrainingAvailableDataInDays)` Indicates the number of days of data used in the most recent scheduled retraining run.
`DescribeModelResult`	`withLatestScheduledRetrainingFailedReason(String latestScheduledRetrainingFailedReason)` If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
`DescribeModelResult`	`withLatestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion)` Indicates the most recent model version that was generated by retraining.
`DescribeModelResult`	`withLatestScheduledRetrainingStartTime(Date latestScheduledRetrainingStartTime)` Indicates the start time of the most recent scheduled retraining run.
`DescribeModelResult`	`withLatestScheduledRetrainingStatus(ModelVersionStatus latestScheduledRetrainingStatus)` Indicates the status of the most recent scheduled retraining run.
`DescribeModelResult`	`withLatestScheduledRetrainingStatus(String latestScheduledRetrainingStatus)` Indicates the status of the most recent scheduled retraining run.
`DescribeModelResult`	`withModelArn(String modelArn)` The Amazon Resource Name (ARN) of the machine learning model being described.
`DescribeModelResult`	`withModelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration)` Configuration information for the model's pointwise model diagnostics.
`DescribeModelResult`	`withModelMetrics(String modelMetrics)` The Model Metrics show an aggregated summary of the model's performance within the evaluation time range.
`DescribeModelResult`	`withModelName(String modelName)` The name of the machine learning model being described.
`DescribeModelResult`	`withModelQuality(ModelQuality modelQuality)` Provides a quality assessment for a model that uses labels.
`DescribeModelResult`	`withModelQuality(String modelQuality)` Provides a quality assessment for a model that uses labels.
`DescribeModelResult`	`withModelVersionActivatedAt(Date modelVersionActivatedAt)` The date the active model version was activated.
`DescribeModelResult`	`withNextScheduledRetrainingStartDate(Date nextScheduledRetrainingStartDate)` Indicates the date and time that the next scheduled retraining run will start on.
`DescribeModelResult`	`withOffCondition(String offCondition)` Indicates that the asset associated with this sensor has been shut off.
`DescribeModelResult`	`withPreviousActiveModelVersion(Long previousActiveModelVersion)` The model version that was set as the active model version prior to the current active model version.
`DescribeModelResult`	`withPreviousActiveModelVersionArn(String previousActiveModelVersionArn)` The ARN of the model version that was set as the active model version prior to the current active model version.
`DescribeModelResult`	`withPreviousModelVersionActivatedAt(Date previousModelVersionActivatedAt)` The date and time when the previous active model version was activated.
`DescribeModelResult`	`withPriorModelMetrics(String priorModelMetrics)` If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range.
`DescribeModelResult`	`withRetrainingSchedulerStatus(RetrainingSchedulerStatus retrainingSchedulerStatus)` Indicates the status of the retraining scheduler.
`DescribeModelResult`	`withRetrainingSchedulerStatus(String retrainingSchedulerStatus)` Indicates the status of the retraining scheduler.
`DescribeModelResult`	`withRoleArn(String roleArn)` The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
`DescribeModelResult`	`withSchema(String schema)` A JSON description of the data that is in each time series dataset, including names, column names, and data types.
`DescribeModelResult`	`withServerSideKmsKeyId(String serverSideKmsKeyId)` Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
`DescribeModelResult`	`withSourceModelVersionArn(String sourceModelVersionArn)` The Amazon Resource Name (ARN) of the source model version.
`DescribeModelResult`	`withStatus(ModelStatus status)` Specifies the current status of the model being described.
`DescribeModelResult`	`withStatus(String status)` Specifies the current status of the model being described.
`DescribeModelResult`	`withTrainingDataEndTime(Date trainingDataEndTime)` Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
`DescribeModelResult`	`withTrainingDataStartTime(Date trainingDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
`DescribeModelResult`	`withTrainingExecutionEndTime(Date trainingExecutionEndTime)` Indicates the time at which the training of the machine learning model was completed.
`DescribeModelResult`	`withTrainingExecutionStartTime(Date trainingExecutionStartTime)` Indicates the time at which the training of the machine learning model began.

Methods inherited from class com.amazonaws.AmazonWebServiceResult
getSdkHttpMetadata, getSdkResponseMetadata, setSdkHttpMetadata, setSdkResponseMetadata

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - DescribeModelResult
```
public DescribeModelResult()
```
- Method Detail
  - setModelName
```
public void setModelName(String modelName)
```
    The name of the machine learning model being described.
    
    Parameters:
    
    modelName - The name of the machine learning model being described.
  - getModelName
```
public String getModelName()
```
    The name of the machine learning model being described.
    
    Returns:
    
    The name of the machine learning model being described.
  - withModelName
```
public DescribeModelResult withModelName(String modelName)
```
    The name of the machine learning model being described.
    
    Parameters:
    
    modelName - The name of the machine learning model being described.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setModelArn
```
public void setModelArn(String modelArn)
```
    The Amazon Resource Name (ARN) of the machine learning model being described.
    
    Parameters:
    
    modelArn - The Amazon Resource Name (ARN) of the machine learning model being described.
  - getModelArn
```
public String getModelArn()
```
    The Amazon Resource Name (ARN) of the machine learning model being described.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the machine learning model being described.
  - withModelArn
```
public DescribeModelResult withModelArn(String modelArn)
```
    The Amazon Resource Name (ARN) of the machine learning model being described.
    
    Parameters:
    
    modelArn - The Amazon Resource Name (ARN) of the machine learning model being described.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDatasetName
```
public void setDatasetName(String datasetName)
```
    The name of the dataset being used by the machine learning being described.
    
    Parameters:
    
    datasetName - The name of the dataset being used by the machine learning being described.
  - getDatasetName
```
public String getDatasetName()
```
    The name of the dataset being used by the machine learning being described.
    
    Returns:
    
    The name of the dataset being used by the machine learning being described.
  - withDatasetName
```
public DescribeModelResult withDatasetName(String datasetName)
```
    The name of the dataset being used by the machine learning being described.
    
    Parameters:
    
    datasetName - The name of the dataset being used by the machine learning being described.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDatasetArn
```
public void setDatasetArn(String datasetArn)
```
    The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
    
    Parameters:
    
    datasetArn - The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
  - getDatasetArn
```
public String getDatasetArn()
```
    The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
    
    Returns:
    
    The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
  - withDatasetArn
```
public DescribeModelResult withDatasetArn(String datasetArn)
```
    The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
    
    Parameters:
    
    datasetArn - The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setSchema
```
public void setSchema(String schema)
```
    A JSON description of the data that is in each time series dataset, including names, column names, and data types.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    schema - A JSON description of the data that is in each time series dataset, including names, column names, and data types.
  - getSchema
```
public String getSchema()
```
    A JSON description of the data that is in each time series dataset, including names, column names, and data types.
    
    This field's value will be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    Returns:
    
    A JSON description of the data that is in each time series dataset, including names, column names, and data types.
  - withSchema
```
public DescribeModelResult withSchema(String schema)
```
    A JSON description of the data that is in each time series dataset, including names, column names, and data types.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    schema - A JSON description of the data that is in each time series dataset, including names, column names, and data types.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLabelsInputConfiguration
```
public void setLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)
```
    Specifies configuration information about the labels input, including its S3 location.
    
    Parameters:
    
    labelsInputConfiguration - Specifies configuration information about the labels input, including its S3 location.
  - getLabelsInputConfiguration
```
public LabelsInputConfiguration getLabelsInputConfiguration()
```
    Specifies configuration information about the labels input, including its S3 location.
    
    Returns:
    
    Specifies configuration information about the labels input, including its S3 location.
  - withLabelsInputConfiguration
```
public DescribeModelResult withLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)
```
    Specifies configuration information about the labels input, including its S3 location.
    
    Parameters:
    
    labelsInputConfiguration - Specifies configuration information about the labels input, including its S3 location.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTrainingDataStartTime
```
public void setTrainingDataStartTime(Date trainingDataStartTime)
```
    Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
    
    Parameters:
    
    trainingDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
  - getTrainingDataStartTime
```
public Date getTrainingDataStartTime()
```
    Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
  - withTrainingDataStartTime
```
public DescribeModelResult withTrainingDataStartTime(Date trainingDataStartTime)
```
    Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
    
    Parameters:
    
    trainingDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTrainingDataEndTime
```
public void setTrainingDataEndTime(Date trainingDataEndTime)
```
    Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
    
    Parameters:
    
    trainingDataEndTime - Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
  - getTrainingDataEndTime
```
public Date getTrainingDataEndTime()
```
    Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
  - withTrainingDataEndTime
```
public DescribeModelResult withTrainingDataEndTime(Date trainingDataEndTime)
```
    Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
    
    Parameters:
    
    trainingDataEndTime - Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEvaluationDataStartTime
```
public void setEvaluationDataStartTime(Date evaluationDataStartTime)
```
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
    
    Parameters:
    
    evaluationDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
  - getEvaluationDataStartTime
```
public Date getEvaluationDataStartTime()
```
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
  - withEvaluationDataStartTime
```
public DescribeModelResult withEvaluationDataStartTime(Date evaluationDataStartTime)
```
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
    
    Parameters:
    
    evaluationDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setEvaluationDataEndTime
```
public void setEvaluationDataEndTime(Date evaluationDataEndTime)
```
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
    
    Parameters:
    
    evaluationDataEndTime - Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
  - getEvaluationDataEndTime
```
public Date getEvaluationDataEndTime()
```
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
  - withEvaluationDataEndTime
```
public DescribeModelResult withEvaluationDataEndTime(Date evaluationDataEndTime)
```
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
    
    Parameters:
    
    evaluationDataEndTime - Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setRoleArn
```
public void setRoleArn(String roleArn)
```
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
    
    Parameters:
    
    roleArn - The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
  - getRoleArn
```
public String getRoleArn()
```
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
    
    Returns:
    
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
  - withRoleArn
```
public DescribeModelResult withRoleArn(String roleArn)
```
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
    
    Parameters:
    
    roleArn - The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDataPreProcessingConfiguration
```
public void setDataPreProcessingConfiguration(DataPreProcessingConfiguration dataPreProcessingConfiguration)
```
    The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
    
    Parameters:
    
    dataPreProcessingConfiguration - The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
  - getDataPreProcessingConfiguration
```
public DataPreProcessingConfiguration getDataPreProcessingConfiguration()
```
    The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
    
    Returns:
    
    The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
  - withDataPreProcessingConfiguration
```
public DescribeModelResult withDataPreProcessingConfiguration(DataPreProcessingConfiguration dataPreProcessingConfiguration)
```
    The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
    
    Parameters:
    
    dataPreProcessingConfiguration - The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.
    
    When providing a value for the TargetSamplingRate, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate is PT1H
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setStatus
```
public void setStatus(String status)
```
    Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Parameters:
    
    status - Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    See Also:
    
    ModelStatus
  - getStatus
```
public String getStatus()
```
    Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Returns:
    
    Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    See Also:
    
    ModelStatus
  - withStatus
```
public DescribeModelResult withStatus(String status)
```
    Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Parameters:
    
    status - Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelStatus
  - withStatus
```
public DescribeModelResult withStatus(ModelStatus status)
```
    Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Parameters:
    
    status - Specifies the current status of the model being described. Status describes the status of the most recent action of the model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelStatus
  - setTrainingExecutionStartTime
```
public void setTrainingExecutionStartTime(Date trainingExecutionStartTime)
```
    Indicates the time at which the training of the machine learning model began.
    
    Parameters:
    
    trainingExecutionStartTime - Indicates the time at which the training of the machine learning model began.
  - getTrainingExecutionStartTime
```
public Date getTrainingExecutionStartTime()
```
    Indicates the time at which the training of the machine learning model began.
    
    Returns:
    
    Indicates the time at which the training of the machine learning model began.
  - withTrainingExecutionStartTime
```
public DescribeModelResult withTrainingExecutionStartTime(Date trainingExecutionStartTime)
```
    Indicates the time at which the training of the machine learning model began.
    
    Parameters:
    
    trainingExecutionStartTime - Indicates the time at which the training of the machine learning model began.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTrainingExecutionEndTime
```
public void setTrainingExecutionEndTime(Date trainingExecutionEndTime)
```
    Indicates the time at which the training of the machine learning model was completed.
    
    Parameters:
    
    trainingExecutionEndTime - Indicates the time at which the training of the machine learning model was completed.
  - getTrainingExecutionEndTime
```
public Date getTrainingExecutionEndTime()
```
    Indicates the time at which the training of the machine learning model was completed.
    
    Returns:
    
    Indicates the time at which the training of the machine learning model was completed.
  - withTrainingExecutionEndTime
```
public DescribeModelResult withTrainingExecutionEndTime(Date trainingExecutionEndTime)
```
    Indicates the time at which the training of the machine learning model was completed.
    
    Parameters:
    
    trainingExecutionEndTime - Indicates the time at which the training of the machine learning model was completed.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setFailedReason
```
public void setFailedReason(String failedReason)
```
    If the training of the machine learning model failed, this indicates the reason for that failure.
    
    Parameters:
    
    failedReason - If the training of the machine learning model failed, this indicates the reason for that failure.
  - getFailedReason
```
public String getFailedReason()
```
    If the training of the machine learning model failed, this indicates the reason for that failure.
    
    Returns:
    
    If the training of the machine learning model failed, this indicates the reason for that failure.
  - withFailedReason
```
public DescribeModelResult withFailedReason(String failedReason)
```
    If the training of the machine learning model failed, this indicates the reason for that failure.
    
    Parameters:
    
    failedReason - If the training of the machine learning model failed, this indicates the reason for that failure.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setModelMetrics
```
public void setModelMetrics(String modelMetrics)
```
    The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    modelMetrics - The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
  - getModelMetrics
```
public String getModelMetrics()
```
    The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
    
    This field's value will be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    Returns:
    
    The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
  - withModelMetrics
```
public DescribeModelResult withModelMetrics(String modelMetrics)
```
    The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    modelMetrics - The Model Metrics show an aggregated summary of the model's performance within the evaluation time range. This is the JSON content of the metrics created when evaluating the model.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLastUpdatedTime
```
public void setLastUpdatedTime(Date lastUpdatedTime)
```
    Indicates the last time the machine learning model was updated. The type of update is not specified.
    
    Parameters:
    
    lastUpdatedTime - Indicates the last time the machine learning model was updated. The type of update is not specified.
  - getLastUpdatedTime
```
public Date getLastUpdatedTime()
```
    Indicates the last time the machine learning model was updated. The type of update is not specified.
    
    Returns:
    
    Indicates the last time the machine learning model was updated. The type of update is not specified.
  - withLastUpdatedTime
```
public DescribeModelResult withLastUpdatedTime(Date lastUpdatedTime)
```
    Indicates the last time the machine learning model was updated. The type of update is not specified.
    
    Parameters:
    
    lastUpdatedTime - Indicates the last time the machine learning model was updated. The type of update is not specified.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setCreatedAt
```
public void setCreatedAt(Date createdAt)
```
    Indicates the time and date at which the machine learning model was created.
    
    Parameters:
    
    createdAt - Indicates the time and date at which the machine learning model was created.
  - getCreatedAt
```
public Date getCreatedAt()
```
    Indicates the time and date at which the machine learning model was created.
    
    Returns:
    
    Indicates the time and date at which the machine learning model was created.
  - withCreatedAt
```
public DescribeModelResult withCreatedAt(Date createdAt)
```
    Indicates the time and date at which the machine learning model was created.
    
    Parameters:
    
    createdAt - Indicates the time and date at which the machine learning model was created.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setServerSideKmsKeyId
```
public void setServerSideKmsKeyId(String serverSideKmsKeyId)
```
    Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
    
    Parameters:
    
    serverSideKmsKeyId - Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
  - getServerSideKmsKeyId
```
public String getServerSideKmsKeyId()
```
    Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
    
    Returns:
    
    Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
  - withServerSideKmsKeyId
```
public DescribeModelResult withServerSideKmsKeyId(String serverSideKmsKeyId)
```
    Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
    
    Parameters:
    
    serverSideKmsKeyId - Provides the identifier of the KMS key used to encrypt model data by Amazon Lookout for Equipment.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setOffCondition
```
public void setOffCondition(String offCondition)
```
    Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
    
    Parameters:
    
    offCondition - Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
  - getOffCondition
```
public String getOffCondition()
```
    Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
    
    Returns:
    
    Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
  - withOffCondition
```
public DescribeModelResult withOffCondition(String offCondition)
```
    Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
    
    Parameters:
    
    offCondition - Indicates that the asset associated with this sensor has been shut off. As long as this condition is met, Lookout for Equipment will not use data from this asset for training, evaluation, or inference.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setSourceModelVersionArn
```
public void setSourceModelVersionArn(String sourceModelVersionArn)
```
    The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
    
    Parameters:
    
    sourceModelVersionArn - The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
  - getSourceModelVersionArn
```
public String getSourceModelVersionArn()
```
    The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
  - withSourceModelVersionArn
```
public DescribeModelResult withSourceModelVersionArn(String sourceModelVersionArn)
```
    The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
    
    Parameters:
    
    sourceModelVersionArn - The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setImportJobStartTime
```
public void setImportJobStartTime(Date importJobStartTime)
```
    The date and time when the import job was started. This field appears if the active model version was imported.
    
    Parameters:
    
    importJobStartTime - The date and time when the import job was started. This field appears if the active model version was imported.
  - getImportJobStartTime
```
public Date getImportJobStartTime()
```
    The date and time when the import job was started. This field appears if the active model version was imported.
    
    Returns:
    
    The date and time when the import job was started. This field appears if the active model version was imported.
  - withImportJobStartTime
```
public DescribeModelResult withImportJobStartTime(Date importJobStartTime)
```
    The date and time when the import job was started. This field appears if the active model version was imported.
    
    Parameters:
    
    importJobStartTime - The date and time when the import job was started. This field appears if the active model version was imported.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setImportJobEndTime
```
public void setImportJobEndTime(Date importJobEndTime)
```
    The date and time when the import job was completed. This field appears if the active model version was imported.
    
    Parameters:
    
    importJobEndTime - The date and time when the import job was completed. This field appears if the active model version was imported.
  - getImportJobEndTime
```
public Date getImportJobEndTime()
```
    The date and time when the import job was completed. This field appears if the active model version was imported.
    
    Returns:
    
    The date and time when the import job was completed. This field appears if the active model version was imported.
  - withImportJobEndTime
```
public DescribeModelResult withImportJobEndTime(Date importJobEndTime)
```
    The date and time when the import job was completed. This field appears if the active model version was imported.
    
    Parameters:
    
    importJobEndTime - The date and time when the import job was completed. This field appears if the active model version was imported.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setActiveModelVersion
```
public void setActiveModelVersion(Long activeModelVersion)
```
    The name of the model version used by the inference schedular when running a scheduled inference execution.
    
    Parameters:
    
    activeModelVersion - The name of the model version used by the inference schedular when running a scheduled inference execution.
  - getActiveModelVersion
```
public Long getActiveModelVersion()
```
    The name of the model version used by the inference schedular when running a scheduled inference execution.
    
    Returns:
    
    The name of the model version used by the inference schedular when running a scheduled inference execution.
  - withActiveModelVersion
```
public DescribeModelResult withActiveModelVersion(Long activeModelVersion)
```
    The name of the model version used by the inference schedular when running a scheduled inference execution.
    
    Parameters:
    
    activeModelVersion - The name of the model version used by the inference schedular when running a scheduled inference execution.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setActiveModelVersionArn
```
public void setActiveModelVersionArn(String activeModelVersionArn)
```
    The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
    
    Parameters:
    
    activeModelVersionArn - The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
  - getActiveModelVersionArn
```
public String getActiveModelVersionArn()
```
    The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
  - withActiveModelVersionArn
```
public DescribeModelResult withActiveModelVersionArn(String activeModelVersionArn)
```
    The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
    
    Parameters:
    
    activeModelVersionArn - The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setModelVersionActivatedAt
```
public void setModelVersionActivatedAt(Date modelVersionActivatedAt)
```
    The date the active model version was activated.
    
    Parameters:
    
    modelVersionActivatedAt - The date the active model version was activated.
  - getModelVersionActivatedAt
```
public Date getModelVersionActivatedAt()
```
    The date the active model version was activated.
    
    Returns:
    
    The date the active model version was activated.
  - withModelVersionActivatedAt
```
public DescribeModelResult withModelVersionActivatedAt(Date modelVersionActivatedAt)
```
    The date the active model version was activated.
    
    Parameters:
    
    modelVersionActivatedAt - The date the active model version was activated.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPreviousActiveModelVersion
```
public void setPreviousActiveModelVersion(Long previousActiveModelVersion)
```
    The model version that was set as the active model version prior to the current active model version.
    
    Parameters:
    
    previousActiveModelVersion - The model version that was set as the active model version prior to the current active model version.
  - getPreviousActiveModelVersion
```
public Long getPreviousActiveModelVersion()
```
    The model version that was set as the active model version prior to the current active model version.
    
    Returns:
    
    The model version that was set as the active model version prior to the current active model version.
  - withPreviousActiveModelVersion
```
public DescribeModelResult withPreviousActiveModelVersion(Long previousActiveModelVersion)
```
    The model version that was set as the active model version prior to the current active model version.
    
    Parameters:
    
    previousActiveModelVersion - The model version that was set as the active model version prior to the current active model version.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPreviousActiveModelVersionArn
```
public void setPreviousActiveModelVersionArn(String previousActiveModelVersionArn)
```
    The ARN of the model version that was set as the active model version prior to the current active model version.
    
    Parameters:
    
    previousActiveModelVersionArn - The ARN of the model version that was set as the active model version prior to the current active model version.
  - getPreviousActiveModelVersionArn
```
public String getPreviousActiveModelVersionArn()
```
    The ARN of the model version that was set as the active model version prior to the current active model version.
    
    Returns:
    
    The ARN of the model version that was set as the active model version prior to the current active model version.
  - withPreviousActiveModelVersionArn
```
public DescribeModelResult withPreviousActiveModelVersionArn(String previousActiveModelVersionArn)
```
    The ARN of the model version that was set as the active model version prior to the current active model version.
    
    Parameters:
    
    previousActiveModelVersionArn - The ARN of the model version that was set as the active model version prior to the current active model version.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPreviousModelVersionActivatedAt
```
public void setPreviousModelVersionActivatedAt(Date previousModelVersionActivatedAt)
```
    The date and time when the previous active model version was activated.
    
    Parameters:
    
    previousModelVersionActivatedAt - The date and time when the previous active model version was activated.
  - getPreviousModelVersionActivatedAt
```
public Date getPreviousModelVersionActivatedAt()
```
    The date and time when the previous active model version was activated.
    
    Returns:
    
    The date and time when the previous active model version was activated.
  - withPreviousModelVersionActivatedAt
```
public DescribeModelResult withPreviousModelVersionActivatedAt(Date previousModelVersionActivatedAt)
```
    The date and time when the previous active model version was activated.
    
    Parameters:
    
    previousModelVersionActivatedAt - The date and time when the previous active model version was activated.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPriorModelMetrics
```
public void setPriorModelMetrics(String priorModelMetrics)
```
    If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    priorModelMetrics - If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
  - getPriorModelMetrics
```
public String getPriorModelMetrics()
```
    If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
    
    This field's value will be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    Returns:
    
    If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
  - withPriorModelMetrics
```
public DescribeModelResult withPriorModelMetrics(String priorModelMetrics)
```
    If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
    
    This field's value must be valid JSON according to RFC 7159, including the opening and closing braces. For example: '{"key": "value"}'.
    
    The AWS SDK for Java performs a Base64 encoding on this field before sending this request to the AWS service. Users of the SDK should not perform Base64 encoding on this field.
    
    Parameters:
    
    priorModelMetrics - If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLatestScheduledRetrainingFailedReason
```
public void setLatestScheduledRetrainingFailedReason(String latestScheduledRetrainingFailedReason)
```
    If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
    
    Parameters:
    
    latestScheduledRetrainingFailedReason - If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
  - getLatestScheduledRetrainingFailedReason
```
public String getLatestScheduledRetrainingFailedReason()
```
    If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
    
    Returns:
    
    If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
  - withLatestScheduledRetrainingFailedReason
```
public DescribeModelResult withLatestScheduledRetrainingFailedReason(String latestScheduledRetrainingFailedReason)
```
    If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
    
    Parameters:
    
    latestScheduledRetrainingFailedReason - If the model version was generated by retraining and the training failed, this indicates the reason for that failure.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLatestScheduledRetrainingStatus
```
public void setLatestScheduledRetrainingStatus(String latestScheduledRetrainingStatus)
```
    Indicates the status of the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingStatus - Indicates the status of the most recent scheduled retraining run.
    
    See Also:
    
    ModelVersionStatus
  - getLatestScheduledRetrainingStatus
```
public String getLatestScheduledRetrainingStatus()
```
    Indicates the status of the most recent scheduled retraining run.
    
    Returns:
    
    Indicates the status of the most recent scheduled retraining run.
    
    See Also:
    
    ModelVersionStatus
  - withLatestScheduledRetrainingStatus
```
public DescribeModelResult withLatestScheduledRetrainingStatus(String latestScheduledRetrainingStatus)
```
    Indicates the status of the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingStatus - Indicates the status of the most recent scheduled retraining run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelVersionStatus
  - withLatestScheduledRetrainingStatus
```
public DescribeModelResult withLatestScheduledRetrainingStatus(ModelVersionStatus latestScheduledRetrainingStatus)
```
    Indicates the status of the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingStatus - Indicates the status of the most recent scheduled retraining run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelVersionStatus
  - setLatestScheduledRetrainingModelVersion
```
public void setLatestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion)
```
    Indicates the most recent model version that was generated by retraining.
    
    Parameters:
    
    latestScheduledRetrainingModelVersion - Indicates the most recent model version that was generated by retraining.
  - getLatestScheduledRetrainingModelVersion
```
public Long getLatestScheduledRetrainingModelVersion()
```
    Indicates the most recent model version that was generated by retraining.
    
    Returns:
    
    Indicates the most recent model version that was generated by retraining.
  - withLatestScheduledRetrainingModelVersion
```
public DescribeModelResult withLatestScheduledRetrainingModelVersion(Long latestScheduledRetrainingModelVersion)
```
    Indicates the most recent model version that was generated by retraining.
    
    Parameters:
    
    latestScheduledRetrainingModelVersion - Indicates the most recent model version that was generated by retraining.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLatestScheduledRetrainingStartTime
```
public void setLatestScheduledRetrainingStartTime(Date latestScheduledRetrainingStartTime)
```
    Indicates the start time of the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingStartTime - Indicates the start time of the most recent scheduled retraining run.
  - getLatestScheduledRetrainingStartTime
```
public Date getLatestScheduledRetrainingStartTime()
```
    Indicates the start time of the most recent scheduled retraining run.
    
    Returns:
    
    Indicates the start time of the most recent scheduled retraining run.
  - withLatestScheduledRetrainingStartTime
```
public DescribeModelResult withLatestScheduledRetrainingStartTime(Date latestScheduledRetrainingStartTime)
```
    Indicates the start time of the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingStartTime - Indicates the start time of the most recent scheduled retraining run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLatestScheduledRetrainingAvailableDataInDays
```
public void setLatestScheduledRetrainingAvailableDataInDays(Integer latestScheduledRetrainingAvailableDataInDays)
```
    Indicates the number of days of data used in the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingAvailableDataInDays - Indicates the number of days of data used in the most recent scheduled retraining run.
  - getLatestScheduledRetrainingAvailableDataInDays
```
public Integer getLatestScheduledRetrainingAvailableDataInDays()
```
    Indicates the number of days of data used in the most recent scheduled retraining run.
    
    Returns:
    
    Indicates the number of days of data used in the most recent scheduled retraining run.
  - withLatestScheduledRetrainingAvailableDataInDays
```
public DescribeModelResult withLatestScheduledRetrainingAvailableDataInDays(Integer latestScheduledRetrainingAvailableDataInDays)
```
    Indicates the number of days of data used in the most recent scheduled retraining run.
    
    Parameters:
    
    latestScheduledRetrainingAvailableDataInDays - Indicates the number of days of data used in the most recent scheduled retraining run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setNextScheduledRetrainingStartDate
```
public void setNextScheduledRetrainingStartDate(Date nextScheduledRetrainingStartDate)
```
    Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
    
    Parameters:
    
    nextScheduledRetrainingStartDate - Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
  - getNextScheduledRetrainingStartDate
```
public Date getNextScheduledRetrainingStartDate()
```
    Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
    
    Returns:
    
    Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
  - withNextScheduledRetrainingStartDate
```
public DescribeModelResult withNextScheduledRetrainingStartDate(Date nextScheduledRetrainingStartDate)
```
    Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
    
    Parameters:
    
    nextScheduledRetrainingStartDate - Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAccumulatedInferenceDataStartTime
```
public void setAccumulatedInferenceDataStartTime(Date accumulatedInferenceDataStartTime)
```
    Indicates the start time of the inference data that has been accumulated.
    
    Parameters:
    
    accumulatedInferenceDataStartTime - Indicates the start time of the inference data that has been accumulated.
  - getAccumulatedInferenceDataStartTime
```
public Date getAccumulatedInferenceDataStartTime()
```
    Indicates the start time of the inference data that has been accumulated.
    
    Returns:
    
    Indicates the start time of the inference data that has been accumulated.
  - withAccumulatedInferenceDataStartTime
```
public DescribeModelResult withAccumulatedInferenceDataStartTime(Date accumulatedInferenceDataStartTime)
```
    Indicates the start time of the inference data that has been accumulated.
    
    Parameters:
    
    accumulatedInferenceDataStartTime - Indicates the start time of the inference data that has been accumulated.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAccumulatedInferenceDataEndTime
```
public void setAccumulatedInferenceDataEndTime(Date accumulatedInferenceDataEndTime)
```
    Indicates the end time of the inference data that has been accumulated.
    
    Parameters:
    
    accumulatedInferenceDataEndTime - Indicates the end time of the inference data that has been accumulated.
  - getAccumulatedInferenceDataEndTime
```
public Date getAccumulatedInferenceDataEndTime()
```
    Indicates the end time of the inference data that has been accumulated.
    
    Returns:
    
    Indicates the end time of the inference data that has been accumulated.
  - withAccumulatedInferenceDataEndTime
```
public DescribeModelResult withAccumulatedInferenceDataEndTime(Date accumulatedInferenceDataEndTime)
```
    Indicates the end time of the inference data that has been accumulated.
    
    Parameters:
    
    accumulatedInferenceDataEndTime - Indicates the end time of the inference data that has been accumulated.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setRetrainingSchedulerStatus
```
public void setRetrainingSchedulerStatus(String retrainingSchedulerStatus)
```
    Indicates the status of the retraining scheduler.
    
    Parameters:
    
    retrainingSchedulerStatus - Indicates the status of the retraining scheduler.
    
    See Also:
    
    RetrainingSchedulerStatus
  - getRetrainingSchedulerStatus
```
public String getRetrainingSchedulerStatus()
```
    Indicates the status of the retraining scheduler.
    
    Returns:
    
    Indicates the status of the retraining scheduler.
    
    See Also:
    
    RetrainingSchedulerStatus
  - withRetrainingSchedulerStatus
```
public DescribeModelResult withRetrainingSchedulerStatus(String retrainingSchedulerStatus)
```
    Indicates the status of the retraining scheduler.
    
    Parameters:
    
    retrainingSchedulerStatus - Indicates the status of the retraining scheduler.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    RetrainingSchedulerStatus
  - withRetrainingSchedulerStatus
```
public DescribeModelResult withRetrainingSchedulerStatus(RetrainingSchedulerStatus retrainingSchedulerStatus)
```
    Indicates the status of the retraining scheduler.
    
    Parameters:
    
    retrainingSchedulerStatus - Indicates the status of the retraining scheduler.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    RetrainingSchedulerStatus
  - setModelDiagnosticsOutputConfiguration
```
public void setModelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration)
```
    Configuration information for the model's pointwise model diagnostics.
    
    Parameters:
    
    modelDiagnosticsOutputConfiguration - Configuration information for the model's pointwise model diagnostics.
  - getModelDiagnosticsOutputConfiguration
```
public ModelDiagnosticsOutputConfiguration getModelDiagnosticsOutputConfiguration()
```
    Configuration information for the model's pointwise model diagnostics.
    
    Returns:
    
    Configuration information for the model's pointwise model diagnostics.
  - withModelDiagnosticsOutputConfiguration
```
public DescribeModelResult withModelDiagnosticsOutputConfiguration(ModelDiagnosticsOutputConfiguration modelDiagnosticsOutputConfiguration)
```
    Configuration information for the model's pointwise model diagnostics.
    
    Parameters:
    
    modelDiagnosticsOutputConfiguration - Configuration information for the model's pointwise model diagnostics.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setModelQuality
```
public void setModelQuality(String modelQuality)
```
    Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Parameters:
    
    modelQuality - Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    See Also:
    
    ModelQuality
  - getModelQuality
```
public String getModelQuality()
```
    Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Returns:
    
    Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    See Also:
    
    ModelQuality
  - withModelQuality
```
public DescribeModelResult withModelQuality(String modelQuality)
```
    Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Parameters:
    
    modelQuality - Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelQuality
  - withModelQuality
```
public DescribeModelResult withModelQuality(ModelQuality modelQuality)
```
    Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Parameters:
    
    modelQuality - Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.
    
    If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.
    
    For information about using labels with your models, see Understanding labeling.
    
    For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ModelQuality
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public DescribeModelResult clone()
```
    Overrides:
    
    clone in class Object

AWS SDK for Java 1.x API Reference - 1.12.780

Class DescribeModelResult

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.AmazonWebServiceResult

Methods inherited from class java.lang.Object

Constructor Detail

DescribeModelResult

Method Detail

setModelName

getModelName

withModelName

setModelArn

getModelArn

withModelArn

setDatasetName

getDatasetName

withDatasetName

setDatasetArn

getDatasetArn

withDatasetArn

setSchema

getSchema

withSchema

setLabelsInputConfiguration

getLabelsInputConfiguration

withLabelsInputConfiguration

setTrainingDataStartTime

getTrainingDataStartTime

withTrainingDataStartTime

setTrainingDataEndTime

getTrainingDataEndTime

withTrainingDataEndTime

setEvaluationDataStartTime

getEvaluationDataStartTime

withEvaluationDataStartTime

setEvaluationDataEndTime

getEvaluationDataEndTime

withEvaluationDataEndTime

setRoleArn

getRoleArn

withRoleArn

setDataPreProcessingConfiguration

getDataPreProcessingConfiguration

withDataPreProcessingConfiguration

setStatus

getStatus

withStatus

withStatus

setTrainingExecutionStartTime

getTrainingExecutionStartTime

withTrainingExecutionStartTime

setTrainingExecutionEndTime

getTrainingExecutionEndTime

withTrainingExecutionEndTime

setFailedReason

getFailedReason

withFailedReason

setModelMetrics

getModelMetrics

withModelMetrics

setLastUpdatedTime

getLastUpdatedTime

withLastUpdatedTime

setCreatedAt

getCreatedAt

withCreatedAt

setServerSideKmsKeyId

getServerSideKmsKeyId

withServerSideKmsKeyId

setOffCondition

getOffCondition

withOffCondition

setSourceModelVersionArn

getSourceModelVersionArn

withSourceModelVersionArn

setImportJobStartTime

getImportJobStartTime

withImportJobStartTime

setImportJobEndTime