MLModel (AWS SDK for Java

java.lang.Object
- software.amazon.awssdk.services.machinelearning.model.MLModel

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<MLModel.Builder,MLModel>
```
@Generated(value="software.amazon.awssdk:codegen")
public final class MLModel
extends Object
implements SdkPojo, Serializable, ToCopyableBuilder<MLModel.Builder,MLModel>
```
Represents the output of a GetMLModel operation.

The content consists of the detailed metadata and the current status of the MLModel.

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static interface MLModel.Builder

Nested Classes
Modifier and Type	Class and Description
`static interface`	`MLModel.Builder`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Algorithm`	`algorithm()` The algorithm used to train the `MLModel`.
`String`	`algorithmAsString()` The algorithm used to train the `MLModel`.
`static MLModel.Builder`	`builder()`
`Long`	`computeTime()` Returns the value of the ComputeTime property for this object.
`Instant`	`createdAt()` The time that the `MLModel` was created.
`String`	`createdByIamUser()` The AWS user account from which the `MLModel` was created.
`RealtimeEndpointInfo`	`endpointInfo()` The current endpoint of the `MLModel`.
`boolean`	`equals(Object obj)`
`Instant`	`finishedAt()` Returns the value of the FinishedAt property for this object.
`<T> Optional<T>`	`getValueForField(String fieldName, Class<T> clazz)`
`int`	`hashCode()`
`String`	`inputDataLocationS3()` The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
`Instant`	`lastUpdatedAt()` The time of the most recent edit to the `MLModel`.
`String`	`message()` A description of the most recent details about accessing the `MLModel`.
`String`	`mlModelId()` The ID assigned to the `MLModel` at creation.
`MLModelType`	`mlModelType()` Identifies the `MLModel` category.
`String`	`mlModelTypeAsString()` Identifies the `MLModel` category.
`String`	`name()` A user-supplied name or description of the `MLModel`.
`Float`	`scoreThreshold()` Returns the value of the ScoreThreshold property for this object.
`Instant`	`scoreThresholdLastUpdatedAt()` The time of the most recent edit to the `ScoreThreshold`.
`List<SdkField<?>>`	`sdkFields()`
`static Class<? extends MLModel.Builder>`	`serializableBuilderClass()`
`Long`	`sizeInBytes()` Returns the value of the SizeInBytes property for this object.
`Instant`	`startedAt()` Returns the value of the StartedAt property for this object.
`EntityStatus`	`status()` The current status of an `MLModel`.
`String`	`statusAsString()` The current status of an `MLModel`.
`MLModel.Builder`	`toBuilder()` Take this object and create a builder that contains all of the current property values of this object.
`String`	`toString()`
`String`	`trainingDataSourceId()` The ID of the training `DataSource`.
`Map<String,String>`	`trainingParameters()` A list of the training parameters in the `MLModel`.

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

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy

- Method Detail
  - mlModelId
```
public String mlModelId()
```
    The ID assigned to the MLModel at creation.
    
    Returns:
    
    The ID assigned to the MLModel at creation.
  - trainingDataSourceId
```
public String trainingDataSourceId()
```
    The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId.
    
    Returns:
    
    The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId.
  - createdByIamUser
```
public 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 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 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 String name()
```
    A user-supplied name or description of the MLModel.
    
    Returns:
    
    A user-supplied name or description of the MLModel.
  - status
```
public EntityStatus status()
```
    The current status of an MLModel. This element can have one of the following values:
    - PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel.
    - INPROGRESS - The creation process is underway.
    - FAILED - The request to create an MLModel didn't run to completion. The model isn't usable.
    - COMPLETED - The creation process 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 an MLModel. This element can have one of the following values:
    
    PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel.
    
    INPROGRESS - The creation process is underway.
    
    FAILED - The request to create an MLModel didn't run to completion. The model isn't usable.
    
    COMPLETED - The creation process completed successfully.
    
    DELETED - The MLModel is marked as deleted. It isn't usable.
    See Also:
    
    EntityStatus
  - statusAsString
```
public String statusAsString()
```
    The current status of an MLModel. This element can have one of the following values:
    - PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel.
    - INPROGRESS - The creation process is underway.
    - FAILED - The request to create an MLModel didn't run to completion. The model isn't usable.
    - COMPLETED - The creation process 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 an MLModel. This element can have one of the following values:
    
    PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel.
    
    INPROGRESS - The creation process is underway.
    
    FAILED - The request to create an MLModel didn't run to completion. The model isn't usable.
    
    COMPLETED - The creation process completed successfully.
    
    DELETED - The MLModel is marked as deleted. It isn't usable.
    See Also:
    
    EntityStatus
  - sizeInBytes
```
public Long sizeInBytes()
```
    Returns the value of the SizeInBytes property for this object.
    
    Returns:
    
    The value of the SizeInBytes property for this object.
  - endpointInfo
```
public RealtimeEndpointInfo endpointInfo()
```
    The current endpoint of the MLModel.
    
    Returns:
    
    The current endpoint of the MLModel.
  - trainingParameters
```
public 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 the 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.
    - sgd.l1RegularizationAmount - The coefficient regularization L1 norm, which controls overfitting the data by penalizing large coefficients. This parameter tends to drive coefficients to zero, resulting in 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, which 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.
    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 the 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.
    
    sgd.l1RegularizationAmount - The coefficient regularization L1 norm, which controls overfitting the data by penalizing large coefficients. This parameter tends to drive coefficients to zero, resulting in 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, which 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 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).
  - algorithm
```
public Algorithm algorithm()
```
    The algorithm used to train the MLModel. The following algorithm is supported:
    - SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function.
    If the service returns an enum value that is not available in the current SDK version, algorithm will return Algorithm.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from algorithmAsString().
    Returns:
    The algorithm used to train the MLModel. The following algorithm is supported:
    
    SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function.
    See Also:
    
    Algorithm
  - algorithmAsString
```
public String algorithmAsString()
```
    The algorithm used to train the MLModel. The following algorithm is supported:
    - SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function.
    If the service returns an enum value that is not available in the current SDK version, algorithm will return Algorithm.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from algorithmAsString().
    Returns:
    The algorithm used to train the MLModel. The following algorithm is supported:
    
    SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function.
    See Also:
    
    Algorithm
  - mlModelType
```
public 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 a child-friendly web site?".
    - 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 a child-friendly web site?".
    
    MULTICLASS - Produces one of several possible results. For example, "Is this a HIGH-, LOW-, or MEDIUM-risk trade?".
    See Also:
    
    MLModelType
  - mlModelTypeAsString
```
public 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 a child-friendly web site?".
    - 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 a child-friendly web site?".
    
    MULTICLASS - Produces one of several possible results. For example, "Is this a HIGH-, LOW-, or MEDIUM-risk trade?".
    See Also:
    
    MLModelType
  - scoreThreshold
```
public Float scoreThreshold()
```
    Returns the value of the ScoreThreshold property for this object.
    
    Returns:
    
    The value of the ScoreThreshold property for this object.
  - scoreThresholdLastUpdatedAt
```
public 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.
  - message
```
public 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 Long computeTime()
```
    Returns the value of the ComputeTime property for this object.
    
    Returns:
    
    The value of the ComputeTime property for this object.
  - finishedAt
```
public Instant finishedAt()
```
    Returns the value of the FinishedAt property for this object.
    
    Returns:
    
    The value of the FinishedAt property for this object.
  - startedAt
```
public Instant startedAt()
```
    Returns the value of the StartedAt property for this object.
    
    Returns:
    
    The value of the StartedAt property for this object.
  - toBuilder
```
public MLModel.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<MLModel.Builder,MLModel>
    
    Returns:
    
    a builder for type T
  - builder
```
public static MLModel.Builder builder()
```
  - serializableBuilderClass
```
public static Class<? extends MLModel.Builder> serializableBuilderClass()
```
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - getValueForField
```
public <T> Optional<T> getValueForField(String fieldName,
                                        Class<T> clazz)
```
  - sdkFields
```
public 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.

Class MLModel

Nested Class Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder

Method Detail

mlModelId

trainingDataSourceId

createdByIamUser

createdAt

lastUpdatedAt

name

status

statusAsString

sizeInBytes

endpointInfo

trainingParameters

inputDataLocationS3

algorithm

algorithmAsString

mlModelType

mlModelTypeAsString

scoreThreshold

scoreThresholdLastUpdatedAt

message

computeTime

finishedAt

startedAt

toBuilder

builder

serializableBuilderClass

hashCode

equals

toString

getValueForField

sdkFields