DescribeModelResult (AWS Java SDK for Amazon Lookout for Equipment 1.11.996 API)

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`	`getCreatedAt()` Indicates the time and date at which the ML 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 ML model being described.
`String`	`getDatasetName()` The name of the dataset being used by the ML being described.
`Date`	`getEvaluationDataEndTime()` Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.
`Date`	`getEvaluationDataStartTime()` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.
`String`	`getFailedReason()` If the training of the ML model failed, this indicates the reason for that failure.
`LabelsInputConfiguration`	`getLabelsInputConfiguration()` Specifies configuration information about the labels input, including its S3 location.
`Date`	`getLastUpdatedTime()` Indicates the last time the ML model was updated.
`String`	`getModelArn()` The Amazon Resource Name (ARN) of the ML model being described.
`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 ML model being described.
`String`	`getRoleArn()` The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML 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 AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
`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 ML model.
`Date`	`getTrainingDataStartTime()` Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.
`Date`	`getTrainingExecutionEndTime()` Indicates the time at which the training of the ML model was completed.
`Date`	`getTrainingExecutionStartTime()` Indicates the time at which the training of the ML model began.
`int`	`hashCode()`
`void`	`setCreatedAt(Date createdAt)` Indicates the time and date at which the ML 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 ML model being described.
`void`	`setDatasetName(String datasetName)` The name of the dataset being used by the ML 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 ML model.
`void`	`setEvaluationDataStartTime(Date evaluationDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.
`void`	`setFailedReason(String failedReason)` If the training of the ML model failed, this indicates the reason for that failure.
`void`	`setLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)` Specifies configuration information about the labels input, including its S3 location.
`void`	`setLastUpdatedTime(Date lastUpdatedTime)` Indicates the last time the ML model was updated.
`void`	`setModelArn(String modelArn)` The Amazon Resource Name (ARN) of the ML model being described.
`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 ML model being described.
`void`	`setRoleArn(String roleArn)` The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML 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 AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
`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 ML model.
`void`	`setTrainingDataStartTime(Date trainingDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.
`void`	`setTrainingExecutionEndTime(Date trainingExecutionEndTime)` Indicates the time at which the training of the ML model was completed.
`void`	`setTrainingExecutionStartTime(Date trainingExecutionStartTime)` Indicates the time at which the training of the ML model began.
`String`	`toString()` Returns a string representation of this object.
`DescribeModelResult`	`withCreatedAt(Date createdAt)` Indicates the time and date at which the ML 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 ML model being described.
`DescribeModelResult`	`withDatasetName(String datasetName)` The name of the dataset being used by the ML 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 ML model.
`DescribeModelResult`	`withEvaluationDataStartTime(Date evaluationDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.
`DescribeModelResult`	`withFailedReason(String failedReason)` If the training of the ML model failed, this indicates the reason for that failure.
`DescribeModelResult`	`withLabelsInputConfiguration(LabelsInputConfiguration labelsInputConfiguration)` Specifies configuration information about the labels input, including its S3 location.
`DescribeModelResult`	`withLastUpdatedTime(Date lastUpdatedTime)` Indicates the last time the ML model was updated.
`DescribeModelResult`	`withModelArn(String modelArn)` The Amazon Resource Name (ARN) of the ML model being described.
`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 ML model being described.
`DescribeModelResult`	`withRoleArn(String roleArn)` The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML 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 AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
`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 ML model.
`DescribeModelResult`	`withTrainingDataStartTime(Date trainingDataStartTime)` Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.
`DescribeModelResult`	`withTrainingExecutionEndTime(Date trainingExecutionEndTime)` Indicates the time at which the training of the ML model was completed.
`DescribeModelResult`	`withTrainingExecutionStartTime(Date trainingExecutionStartTime)` Indicates the time at which the training of the ML model began.

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

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

- Constructor Detail
  - DescribeModelResult
```
public DescribeModelResult()
```
- Method Detail
  - setModelName
```
public void setModelName(String modelName)
```
    The name of the ML model being described.
    
    Parameters:
    
    modelName - The name of the ML model being described.
  - getModelName
```
public String getModelName()
```
    The name of the ML model being described.
    
    Returns:
    
    The name of the ML model being described.
  - withModelName
```
public DescribeModelResult withModelName(String modelName)
```
    The name of the ML model being described.
    
    Parameters:
    
    modelName - The name of the ML 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 ML model being described.
    
    Parameters:
    
    modelArn - The Amazon Resource Name (ARN) of the ML model being described.
  - getModelArn
```
public String getModelArn()
```
    The Amazon Resource Name (ARN) of the ML model being described.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the ML model being described.
  - withModelArn
```
public DescribeModelResult withModelArn(String modelArn)
```
    The Amazon Resource Name (ARN) of the ML model being described.
    
    Parameters:
    
    modelArn - The Amazon Resource Name (ARN) of the ML 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 ML being described.
    
    Parameters:
    
    datasetName - The name of the dataset being used by the ML being described.
  - getDatasetName
```
public String getDatasetName()
```
    The name of the dataset being used by the ML being described.
    
    Returns:
    
    The name of the dataset being used by the ML being described.
  - withDatasetName
```
public DescribeModelResult withDatasetName(String datasetName)
```
    The name of the dataset being used by the ML being described.
    
    Parameters:
    
    datasetName - The name of the dataset being used by the ML 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 ML model being described.
    
    Parameters:
    
    datasetArn - The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.
  - getDatasetArn
```
public String getDatasetArn()
```
    The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.
    
    Returns:
    
    The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.
  - withDatasetArn
```
public DescribeModelResult withDatasetArn(String datasetArn)
```
    The Amazon Resouce Name (ARN) of the dataset used to create the ML model being described.
    
    Parameters:
    
    datasetArn - The Amazon Resouce Name (ARN) of the dataset used to create the ML 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 ML model.
    
    Parameters:
    
    trainingDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.
  - getTrainingDataStartTime
```
public Date getTrainingDataStartTime()
```
    Indicates the time reference in the dataset that was used to begin the subset of training data for the ML model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to begin the subset of training data for the ML 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 ML model.
    
    Parameters:
    
    trainingDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of training data for the ML 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 ML model.
    
    Parameters:
    
    trainingDataEndTime - Indicates the time reference in the dataset that was used to end the subset of training data for the ML model.
  - getTrainingDataEndTime
```
public Date getTrainingDataEndTime()
```
    Indicates the time reference in the dataset that was used to end the subset of training data for the ML model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to end the subset of training data for the ML 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 ML model.
    
    Parameters:
    
    trainingDataEndTime - Indicates the time reference in the dataset that was used to end the subset of training data for the ML 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 ML model.
    
    Parameters:
    
    evaluationDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.
  - getEvaluationDataStartTime
```
public Date getEvaluationDataStartTime()
```
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML 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 ML model.
    
    Parameters:
    
    evaluationDataStartTime - Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the ML 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 ML model.
    
    Parameters:
    
    evaluationDataEndTime - Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.
  - getEvaluationDataEndTime
```
public Date getEvaluationDataEndTime()
```
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML model.
    
    Returns:
    
    Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML 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 ML model.
    
    Parameters:
    
    evaluationDataEndTime - Indicates the time reference in the dataset that was used to end the subset of evaluation data for the ML 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 ML model being described.
    
    Parameters:
    
    roleArn - The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described.
  - getRoleArn
```
public String getRoleArn()
```
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML model being described.
    
    Returns:
    
    The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML 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 ML model being described.
    
    Parameters:
    
    roleArn - The Amazon Resource Name (ARN) of a role with permission to access the data source for the ML 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 ML model began.
    
    Parameters:
    
    trainingExecutionStartTime - Indicates the time at which the training of the ML model began.
  - getTrainingExecutionStartTime
```
public Date getTrainingExecutionStartTime()
```
    Indicates the time at which the training of the ML model began.
    
    Returns:
    
    Indicates the time at which the training of the ML model began.
  - withTrainingExecutionStartTime
```
public DescribeModelResult withTrainingExecutionStartTime(Date trainingExecutionStartTime)
```
    Indicates the time at which the training of the ML model began.
    
    Parameters:
    
    trainingExecutionStartTime - Indicates the time at which the training of the ML 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 ML model was completed.
    
    Parameters:
    
    trainingExecutionEndTime - Indicates the time at which the training of the ML model was completed.
  - getTrainingExecutionEndTime
```
public Date getTrainingExecutionEndTime()
```
    Indicates the time at which the training of the ML model was completed.
    
    Returns:
    
    Indicates the time at which the training of the ML model was completed.
  - withTrainingExecutionEndTime
```
public DescribeModelResult withTrainingExecutionEndTime(Date trainingExecutionEndTime)
```
    Indicates the time at which the training of the ML model was completed.
    
    Parameters:
    
    trainingExecutionEndTime - Indicates the time at which the training of the ML 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 ML model failed, this indicates the reason for that failure.
    
    Parameters:
    
    failedReason - If the training of the ML model failed, this indicates the reason for that failure.
  - getFailedReason
```
public String getFailedReason()
```
    If the training of the ML model failed, this indicates the reason for that failure.
    
    Returns:
    
    If the training of the ML model failed, this indicates the reason for that failure.
  - withFailedReason
```
public DescribeModelResult withFailedReason(String failedReason)
```
    If the training of the ML model failed, this indicates the reason for that failure.
    
    Parameters:
    
    failedReason - If the training of the ML 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 ML model was updated. The type of update is not specified.
    
    Parameters:
    
    lastUpdatedTime - Indicates the last time the ML model was updated. The type of update is not specified.
  - getLastUpdatedTime
```
public Date getLastUpdatedTime()
```
    Indicates the last time the ML model was updated. The type of update is not specified.
    
    Returns:
    
    Indicates the last time the ML model was updated. The type of update is not specified.
  - withLastUpdatedTime
```
public DescribeModelResult withLastUpdatedTime(Date lastUpdatedTime)
```
    Indicates the last time the ML model was updated. The type of update is not specified.
    
    Parameters:
    
    lastUpdatedTime - Indicates the last time the ML 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 ML model was created.
    
    Parameters:
    
    createdAt - Indicates the time and date at which the ML model was created.
  - getCreatedAt
```
public Date getCreatedAt()
```
    Indicates the time and date at which the ML model was created.
    
    Returns:
    
    Indicates the time and date at which the ML model was created.
  - withCreatedAt
```
public DescribeModelResult withCreatedAt(Date createdAt)
```
    Indicates the time and date at which the ML model was created.
    
    Parameters:
    
    createdAt - Indicates the time and date at which the ML 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 AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
    
    Parameters:
    
    serverSideKmsKeyId - Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
  - getServerSideKmsKeyId
```
public String getServerSideKmsKeyId()
```
    Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
    
    Returns:
    
    Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
  - withServerSideKmsKeyId
```
public DescribeModelResult withServerSideKmsKeyId(String serverSideKmsKeyId)
```
    Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment.
    
    Parameters:
    
    serverSideKmsKeyId - Provides the identifier of the AWS KMS customer master key (CMK) 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.
  - 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

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

toString

equals

hashCode

clone