Class: Aws::MachineLearning::Types::MLModel

Inherits:

Struct

• Object
• Struct
• Aws::MachineLearning::Types::MLModel

Defined in:

gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb

Overview

Represents the output of a GetMLModel operation.

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

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #algorithm ⇒ String

  The algorithm used to train the MLModel.

• #compute_time ⇒ Integer

  Long integer type that is a 64-bit signed number.

• #created_at ⇒ Time

  The time that the MLModel was created.

• #created_by_iam_user ⇒ String

  The AWS user account from which the MLModel was created.

• #endpoint_info ⇒ Types::RealtimeEndpointInfo

  The current endpoint of the MLModel.

• #finished_at ⇒ Time

  A timestamp represented in epoch time.

• #input_data_location_s3 ⇒ String

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

• #last_updated_at ⇒ Time

  The time of the most recent edit to the MLModel.

• #message ⇒ String

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

• #ml_model_id ⇒ String

  The ID assigned to the MLModel at creation.

• #ml_model_type ⇒ String

  Identifies the MLModel category.

• #name ⇒ String

  A user-supplied name or description of the MLModel.

• #score_threshold ⇒ Float
• #score_threshold_last_updated_at ⇒ Time

  The time of the most recent edit to the ScoreThreshold.

• #size_in_bytes ⇒ Integer

  Long integer type that is a 64-bit signed number.

• #started_at ⇒ Time

  A timestamp represented in epoch time.

• #status ⇒ String

  The current status of an MLModel.

• #training_data_source_id ⇒ String

  The ID of the training DataSource.

• #training_parameters ⇒ Hash<String,String>

  A list of the training parameters in the MLModel.

Instance Attribute Details

#algorithm ⇒ String

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.

^

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#compute_time ⇒ Integer

Long integer type that is a 64-bit signed number.

Returns:

• (Integer)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#created_at ⇒ Time

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

Returns:

• (Time)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#created_by_iam_user ⇒ String

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:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#endpoint_info ⇒ Types::RealtimeEndpointInfo

The current endpoint of the MLModel.

Returns:

• (Types::RealtimeEndpointInfo)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#finished_at ⇒ Time

A timestamp represented in epoch time.

Returns:

• (Time)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#input_data_location_s3 ⇒ String

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

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#last_updated_at ⇒ Time

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

Returns:

• (Time)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#message ⇒ String

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

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#ml_model_id ⇒ String

The ID assigned to the MLModel at creation.

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#ml_model_type ⇒ String

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?".

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#name ⇒ String

A user-supplied name or description of the MLModel.

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#score_threshold ⇒ Float

Returns:

• (Float)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#score_threshold_last_updated_at ⇒ Time

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

Returns:

• (Time)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#size_in_bytes ⇒ Integer

Long integer type that is a 64-bit signed number.

Returns:

• (Integer)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#started_at ⇒ Time

A timestamp represented in epoch time.

Returns:

• (Time)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#status ⇒ String

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.

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#training_data_source_id ⇒ String

The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId.

Returns:

• (String)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end

#training_parameters ⇒ Hash<String,String>

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.

Returns:

• (Hash<String,String>)

# File 'gems/aws-sdk-machinelearning/lib/aws-sdk-machinelearning/types.rb', line 2593

class MLModel < Struct.new(
  :ml_model_id,
  :training_data_source_id,
  :created_by_iam_user,
  :created_at,
  :last_updated_at,
  :name,
  :status,
  :size_in_bytes,
  :endpoint_info,
  :training_parameters,
  :input_data_location_s3,
  :algorithm,
  :ml_model_type,
  :score_threshold,
  :score_threshold_last_updated_at,
  :message,
  :compute_time,
  :finished_at,
  :started_at)
  SENSITIVE = []
  include Aws::Structure
end