Package software.amazon.awssdk.services.machinelearning.model

Class GetMlModelResponse

java.lang.Object
software.amazon.awssdk.core.SdkResponse
software.amazon.awssdk.awscore.AwsResponse
software.amazon.awssdk.services.machinelearning.model.MachineLearningResponse
software.amazon.awssdk.services.machinelearning.model.GetMlModelResponse
All Implemented Interfaces:
SdkPojo, ToCopyableBuilder<GetMlModelResponse.Builder,GetMlModelResponse>
@Generated("software.amazon.awssdk:codegen") public final class GetMlModelResponse extends MachineLearningResponse implements ToCopyableBuilder<GetMlModelResponse.Builder,GetMlModelResponse>

Represents the output of a GetMLModel operation, and provides detailed information about a MLModel.

  • Method Details

    • mlModelId

      public final String mlModelId()

      The MLModel ID, which is same as the MLModelId in the request.

      Returns:
      The MLModel ID, which is same as the MLModelId in the request.

    • trainingDataSourceId

      public final String trainingDataSourceId()

      The ID of the training DataSource.

      Returns:
      The ID of the training DataSource.

    • createdByIamUser

      public final String createdByIamUser()

      The AWS user account from which the MLModel was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

      Returns:
      The AWS user account from which the MLModel was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

    • createdAt

      public final Instant createdAt()

      The time that the MLModel was created. The time is expressed in epoch time.

      Returns:
      The time that the MLModel was created. The time is expressed in epoch time.

    • lastUpdatedAt

      public final Instant lastUpdatedAt()

      The time of the most recent edit to the MLModel. The time is expressed in epoch time.

      Returns:
      The time of the most recent edit to the MLModel. The time is expressed in epoch time.

    • name

      public final String name()

      A user-supplied name or description of the MLModel.

      Returns:
      A user-supplied name or description of the MLModel.

    • status

      public final EntityStatus status()

      The current status of the MLModel. This element can have one of the following values:

      • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to describe a MLModel .

      • INPROGRESS - The request is processing.

      • FAILED - The request did not run to completion. The ML model isn't usable.

      • COMPLETED - The request completed successfully.

      • DELETED - The MLModel is marked as deleted. It isn't usable.

      If the service returns an enum value that is not available in the current SDK version, status will return EntityStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from statusAsString().

      Returns:
      The current status of the MLModel. This element can have one of the following values:

      • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to describe a MLModel.

      • INPROGRESS - The request is processing.

      • FAILED - The request did not run to completion. The ML model isn't usable.

      • COMPLETED - The request completed successfully.

      • DELETED - The MLModel is marked as deleted. It isn't usable.

      See Also:

    • statusAsString

      public final String statusAsString()

      The current status of the MLModel. This element can have one of the following values:

      • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to describe a MLModel .

      • INPROGRESS - The request is processing.

      • FAILED - The request did not run to completion. The ML model isn't usable.

      • COMPLETED - The request completed successfully.

      • DELETED - The MLModel is marked as deleted. It isn't usable.

      If the service returns an enum value that is not available in the current SDK version, status will return EntityStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from statusAsString().

      Returns:
      The current status of the MLModel. This element can have one of the following values:

      • PENDING - Amazon Machine Learning (Amazon ML) submitted a request to describe a MLModel.

      • INPROGRESS - The request is processing.

      • FAILED - The request did not run to completion. The ML model isn't usable.

      • COMPLETED - The request completed successfully.

      • DELETED - The MLModel is marked as deleted. It isn't usable.

      See Also:

    • sizeInBytes

      public final Long sizeInBytes()
      Returns the value of the SizeInBytes property for this object.
      Returns:
      The value of the SizeInBytes property for this object.

    • endpointInfo

      public final RealtimeEndpointInfo endpointInfo()

      The current endpoint of the MLModel

      Returns:
      The current endpoint of the MLModel

    • hasTrainingParameters

      public final boolean hasTrainingParameters()
      For responses, this returns true if the service returned a value for the TrainingParameters property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

    • trainingParameters

      public final Map<String,String> trainingParameters()

      A list of the training parameters in the MLModel. The list is implemented as a map of key-value pairs.

      The following is the current set of training parameters:

      • sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance.

        The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432.

      • sgd.maxPasses - The number of times that the training process traverses the observations to build the MLModel. The value is an integer that ranges from 1 to 10000. The default value is 10.

      • sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling data improves a model's ability to find the optimal solution for a variety of data types. The valid values are auto and none. The default value is none. We strongly recommend that you shuffle your data.

      • sgd.l1RegularizationAmount - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as 1.0E-08.

        The value is a double that ranges from 0 to MAX_DOUBLE. The default is to not use L1 normalization. This parameter can't be used when L2 is specified. Use this parameter sparingly.

      • sgd.l2RegularizationAmount - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as 1.0E-08.

        The value is a double that ranges from 0 to MAX_DOUBLE. The default is to not use L2 normalization. This parameter can't be used when L1 is specified. Use this parameter sparingly.

      Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

      This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasTrainingParameters() method.

      Returns:
      A list of the training parameters in the MLModel. The list is implemented as a map of key-value pairs.

      The following is the current set of training parameters:

      • sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance.

        The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432.

      • sgd.maxPasses - The number of times that the training process traverses the observations to build the MLModel. The value is an integer that ranges from 1 to 10000. The default value is 10.

      • sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling data improves a model's ability to find the optimal solution for a variety of data types. The valid values are auto and none. The default value is none. We strongly recommend that you shuffle your data.

      • sgd.l1RegularizationAmount - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as 1.0E-08.

        The value is a double that ranges from 0 to MAX_DOUBLE. The default is to not use L1 normalization. This parameter can't be used when L2 is specified. Use this parameter sparingly.

      • sgd.l2RegularizationAmount - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as 1.0E-08.

        The value is a double that ranges from 0 to MAX_DOUBLE. The default is to not use L2 normalization. This parameter can't be used when L1 is specified. Use this parameter sparingly.

    • inputDataLocationS3

      public final String inputDataLocationS3()

      The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

      Returns:
      The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

    • mlModelType

      public final MLModelType mlModelType()

      Identifies the MLModel category. The following are the available types:

      • REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?"

      • BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?"

      • MULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?"

      If the service returns an enum value that is not available in the current SDK version, mlModelType will return MLModelType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from mlModelTypeAsString().

      Returns:
      Identifies the MLModel category. The following are the available types:

      • REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?"

      • BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?"

      • MULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?"

      See Also:

    • mlModelTypeAsString

      public final String mlModelTypeAsString()

      Identifies the MLModel category. The following are the available types:

      • REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?"

      • BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?"

      • MULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?"

      If the service returns an enum value that is not available in the current SDK version, mlModelType will return MLModelType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from mlModelTypeAsString().

      Returns:
      Identifies the MLModel category. The following are the available types:

      • REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?"

      • BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?"

      • MULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?"

      See Also:

    • scoreThreshold

      public final Float scoreThreshold()

      The scoring threshold is used in binary classification MLModel models. It marks the boundary between a positive prediction and a negative prediction.

      Output values greater than or equal to the threshold receive a positive result from the MLModel, such as true. Output values less than the threshold receive a negative response from the MLModel, such as false.

      Returns:
      The scoring threshold is used in binary classification MLModel models. It marks the boundary between a positive prediction and a negative prediction.

      Output values greater than or equal to the threshold receive a positive result from the MLModel, such as true. Output values less than the threshold receive a negative response from the MLModel, such as false.

    • scoreThresholdLastUpdatedAt

      public final Instant scoreThresholdLastUpdatedAt()

      The time of the most recent edit to the ScoreThreshold. The time is expressed in epoch time.

      Returns:
      The time of the most recent edit to the ScoreThreshold. The time is expressed in epoch time.

    • logUri

      public final String logUri()

      A link to the file that contains logs of the CreateMLModel operation.

      Returns:
      A link to the file that contains logs of the CreateMLModel operation.

    • message

      public final String message()

      A description of the most recent details about accessing the MLModel.

      Returns:
      A description of the most recent details about accessing the MLModel.

    • computeTime

      public final Long computeTime()

      The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the MLModel, normalized and scaled on computation resources. ComputeTime is only available if the MLModel is in the COMPLETED state.

      Returns:
      The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the MLModel, normalized and scaled on computation resources. ComputeTime is only available if the MLModel is in the COMPLETED state.

    • finishedAt

      public final Instant finishedAt()

      The epoch time when Amazon Machine Learning marked the MLModel as COMPLETED or FAILED. FinishedAt is only available when the MLModel is in the COMPLETED or FAILED state.

      Returns:
      The epoch time when Amazon Machine Learning marked the MLModel as COMPLETED or FAILED. FinishedAt is only available when the MLModel is in the COMPLETED or FAILED state.

    • startedAt

      public final Instant startedAt()

      The epoch time when Amazon Machine Learning marked the MLModel as INPROGRESS. StartedAt isn't available if the MLModel is in the PENDING state.

      Returns:
      The epoch time when Amazon Machine Learning marked the MLModel as INPROGRESS. StartedAt isn't available if the MLModel is in the PENDING state.

    • recipe

      public final String recipe()

      The recipe to use when training the MLModel. The Recipe provides detailed information about the observation data to use during training, and manipulations to perform on the observation data during training.

      Note: This parameter is provided as part of the verbose format.

      Returns:
      The recipe to use when training the MLModel. The Recipe provides detailed information about the observation data to use during training, and manipulations to perform on the observation data during training.

      Note: This parameter is provided as part of the verbose format.

    • schema

      public final String schema()

      The schema used by all of the data files referenced by the DataSource.

      Note: This parameter is provided as part of the verbose format.

      Returns:
      The schema used by all of the data files referenced by the DataSource.

      Note: This parameter is provided as part of the verbose format.

    • toBuilder

      public GetMlModelResponse.Builder toBuilder()
      Description copied from interface: ToCopyableBuilder
      Take this object and create a builder that contains all of the current property values of this object.
      Specified by:
      toBuilder in interface ToCopyableBuilder<GetMlModelResponse.Builder,GetMlModelResponse>
      Specified by:
      toBuilder in class AwsResponse
      Returns:
      a builder for type T

    • builder

      public static GetMlModelResponse.Builder builder()

    • serializableBuilderClass

      public static Class<? extends GetMlModelResponse.Builder> serializableBuilderClass()

    • hashCode

      public final int hashCode()
      Overrides:
      hashCode in class AwsResponse

    • equals

      public final boolean equals(Object obj)
      Overrides:
      equals in class AwsResponse

    • equalsBySdkFields

      public final boolean equalsBySdkFields(Object obj)
      Description copied from interface: SdkPojo
      Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in an SdkPojo class, and is generated based on a service model.

      If an SdkPojo class does not have any inherited fields, equalsBySdkFields and equals are essentially the same.

      Specified by:
      equalsBySdkFields in interface SdkPojo
      Parameters:
      obj - the object to be compared with
      Returns:
      true if the other object equals to this object by sdk fields, false otherwise.

    • toString

      public final 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

    • getValueForField

      public final <T> Optional<T> getValueForField(String fieldName, Class<T> clazz)
      Description copied from class: SdkResponse
      Used to retrieve the value of a field from any class that extends SdkResponse. The field name specified should match the member name from the corresponding service-2.json model specified in the codegen-resources folder for a given service. The class specifies what class to cast the returned value to. If the returned value is also a modeled class, the SdkResponse.getValueForField(String, Class) method will again be available.
      Overrides:
      getValueForField in class SdkResponse
      Parameters:
      fieldName - The name of the member to be retrieved.
      clazz - The class to cast the returned object to.
      Returns:
      Optional containing the casted return value

    • sdkFields

      public final List<SdkField<?>> sdkFields()
      Specified by:
      sdkFields in interface SdkPojo
      Returns:
      List of SdkField in this POJO. May be empty list but should never be null.