Serialized Form (AWS SDK for Android - Amazon Machine Learning 2.6.7 API)

Package com.amazonaws.services.machinelearning.model
- Class com.amazonaws.services.machinelearning.model.GetMLModelRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - mLModelId
```
String mLModelId
```
      The ID assigned to the MLModel at creation.
      
      Constraints:
      Length: 1 - 64
      Pattern: [a-zA-Z0-9_.-]+
    - verbose
```
Boolean verbose
```
      Specifies whether the GetMLModel operation should return Recipe.
      
      If true, Recipe is returned.
      
      If false, Recipe is not returned.
- Class com.amazonaws.services.machinelearning.model.GetMLModelResult extends Object implements Serializable
  - Serialized Fields
    - mLModelId
```
String mLModelId
```
      The MLModel ID, which is same as the MLModelId in the request.
      
      Constraints:
      Length: 1 - 64
      Pattern: [a-zA-Z0-9_.-]+
    - trainingDataSourceId
```
String trainingDataSourceId
```
      The ID of the training DataSource.
      
      Constraints:
      Length: 1 - 64
      Pattern: [a-zA-Z0-9_.-]+
    - createdByIamUser
```
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.
      
      Constraints:
      Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))
    - createdAt
```
Date createdAt
```
      The time that the MLModel was created. The time is expressed in epoch time.
    - lastUpdatedAt
```
Date lastUpdatedAt
```
      The time of the most recent edit to the MLModel. The time is expressed in epoch time.
    - name
```
String name
```
      A user-supplied name or description of the MLModel.
      
      Constraints:
      Length: - 1024
    - status
```
String 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.
      
      Constraints:
      Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
    - sizeInBytes
```
Long sizeInBytes
```
      Long integer type that is a 64-bit signed number.
    - endpointInfo
```
RealtimeEndpointInfo endpointInfo
```
      The current endpoint of the MLModel
    - trainingParameters
```
Map<K,V> 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.
    - inputDataLocationS3
```
String inputDataLocationS3
```
      The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
      
      Constraints:
      Length: - 2048
      Pattern: s3://([^/]+)(/.*)?
    - mLModelType
```
String 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?"
      
      Constraints:
      Allowed Values: REGRESSION, BINARY, MULTICLASS
    - scoreThreshold
```
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.
    - scoreThresholdLastUpdatedAt
```
Date scoreThresholdLastUpdatedAt
```
      The time of the most recent edit to the ScoreThreshold. The time is expressed in epoch time.
    - logUri
```
String logUri
```
      A link to the file that contains logs of the CreateMLModel operation.
    - message
```
String message
```
      A description of the most recent details about accessing the MLModel.
      
      Constraints:
      Length: - 10240
    - recipe
```
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.
      
      Constraints:
      Length: - 131071
    - schema
```
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.
      
      Constraints:
      Length: - 131071
- Class com.amazonaws.services.machinelearning.model.InternalServerException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - code
```
Integer code
```
- Class com.amazonaws.services.machinelearning.model.InvalidInputException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - code
```
Integer code
```
- Class com.amazonaws.services.machinelearning.model.LimitExceededException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - code
```
Integer code
```
- Class com.amazonaws.services.machinelearning.model.Prediction extends Object implements Serializable
  - Serialized Fields
    - predictedLabel
```
String predictedLabel
```
      The prediction label for either a BINARY or MULTICLASS MLModel.
      
      Constraints:
      Length: 1 -
    - predictedValue
```
Float predictedValue
```
      The prediction value for REGRESSION MLModel.
    - predictedScores
```
Map<K,V> predictedScores
```
      Provides the raw classification score corresponding to each label.
    - details
```
Map<K,V> details
```
      Provides any additional details regarding the prediction.
- Class com.amazonaws.services.machinelearning.model.PredictorNotMountedException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
- Class com.amazonaws.services.machinelearning.model.PredictRequest extends AmazonWebServiceRequest implements Serializable
  - Serialized Fields
    - mLModelId
```
String mLModelId
```
      A unique identifier of the MLModel.
      
      Constraints:
      Length: 1 - 64
      Pattern: [a-zA-Z0-9_.-]+
    - record
```
Map<K,V> record
```
      A map of variable name-value pairs that represent an observation.
    - predictEndpoint
```
String predictEndpoint
```
      The new value for the predictEndpoint property for this object.
      Constraints:
      Length: - 2048
      Pattern: https://[a-zA-Z0-9-.]*\.amazon(aws)?\.com[/]?
- Class com.amazonaws.services.machinelearning.model.PredictResult extends Object implements Serializable
  - Serialized Fields
    - prediction
```
Prediction prediction
```
      The output from a Predict operation:
      
      Details - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | MULTICLASS DetailsAttributes.ALGORITHM - SGD
      
      PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request.
      
      PredictedScores - Contains the raw classification score corresponding to each label.
      
      PredictedValue - Present for a REGRESSION MLModel request.
- Class com.amazonaws.services.machinelearning.model.RealtimeEndpointInfo extends Object implements Serializable
  - Serialized Fields
    - peakRequestsPerSecond
```
Integer peakRequestsPerSecond
```
      The maximum processing rate for the real-time endpoint for MLModel, measured in incoming requests per second.
    - createdAt
```
Date createdAt
```
      The time that the request to create the real-time endpoint for the MLModel was received. The time is expressed in epoch time.
    - endpointUrl
```
String endpointUrl
```
      The URI that specifies where to send real-time prediction requests for the MLModel.
      Note
      The application must wait until the real-time endpoint is ready before using this URI.
      
      Constraints:
      Length: - 2048
      Pattern: https://[a-zA-Z0-9-.]*\.amazon(aws)?\.com[/]?
    - endpointStatus
```
String endpointStatus
```
      The current status of the real-time endpoint for the MLModel . This element can have one of the following values:
      
      NONE - Endpoint does not exist or was previously deleted.
      
      READY - Endpoint is ready to be used for real-time predictions.
      
      UPDATING - Updating/creating the endpoint.
      
      Constraints:
      Allowed Values: NONE, READY, UPDATING, FAILED
- Class com.amazonaws.services.machinelearning.model.ResourceNotFoundException extends AmazonServiceException implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - code
```
Integer code
```

Serialized Form

Package com.amazonaws.services.machinelearning.model

Class com.amazonaws.services.machinelearning.model.GetMLModelRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

mLModelId

verbose

Class com.amazonaws.services.machinelearning.model.GetMLModelResult extends Object implements Serializable

Serialized Fields

mLModelId

trainingDataSourceId

createdByIamUser

createdAt

lastUpdatedAt

name

status

sizeInBytes

endpointInfo

trainingParameters

inputDataLocationS3

mLModelType

scoreThreshold

scoreThresholdLastUpdatedAt

logUri

message

recipe

schema

Class com.amazonaws.services.machinelearning.model.InternalServerException extends AmazonServiceException implements Serializable

Serialized Fields

code

Class com.amazonaws.services.machinelearning.model.InvalidInputException extends AmazonServiceException implements Serializable

Serialized Fields

code

Class com.amazonaws.services.machinelearning.model.LimitExceededException extends AmazonServiceException implements Serializable

Serialized Fields

code

Class com.amazonaws.services.machinelearning.model.Prediction extends Object implements Serializable

Serialized Fields

predictedLabel

predictedValue

predictedScores

details

Class com.amazonaws.services.machinelearning.model.PredictorNotMountedException extends AmazonServiceException implements Serializable

Class com.amazonaws.services.machinelearning.model.PredictRequest extends AmazonWebServiceRequest implements Serializable

Serialized Fields

mLModelId

record

predictEndpoint

Class com.amazonaws.services.machinelearning.model.PredictResult extends Object implements Serializable

Serialized Fields

prediction

Class com.amazonaws.services.machinelearning.model.RealtimeEndpointInfo extends Object implements Serializable

Serialized Fields

peakRequestsPerSecond

createdAt

endpointUrl

endpointStatus

Class com.amazonaws.services.machinelearning.model.ResourceNotFoundException extends AmazonServiceException implements Serializable

Serialized Fields

code