AWS SDK for Go (PILOT)
API Reference

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MLModel

import "github.com/aws/aws-sdk-go/service/machinelearning"

type MLModel struct { Algorithm *string `type:"string" enum:"Algorithm"` ComputeTime *int64 `type:"long"` CreatedAt *time.Time `type:"timestamp"` CreatedByIamUser *string `type:"string"` EndpointInfo *RealtimeEndpointInfo `type:"structure"` FinishedAt *time.Time `type:"timestamp"` InputDataLocationS3 *string `type:"string"` LastUpdatedAt *time.Time `type:"timestamp"` MLModelId *string `min:"1" type:"string"` MLModelType *string `type:"string" enum:"MLModelType"` Message *string `type:"string"` Name *string `type:"string"` ScoreThreshold *float64 `type:"float"` ScoreThresholdLastUpdatedAt *time.Time `type:"timestamp"` SizeInBytes *int64 `type:"long"` StartedAt *time.Time `type:"timestamp"` Status *string `type:"string" enum:"EntityStatus"` TrainingDataSourceId *string `min:"1" type:"string"` TrainingParameters map[string]*string `type:"map"` }

Represents the output of a GetMLModel operation.

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

Algorithm

Type: *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.

ComputeTime

Type: *int64

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

CreatedAt

Type: *time.Time

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

CreatedByIamUser

Type: *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.

EndpointInfo

Describes the real-time endpoint information for an MLModel.

FinishedAt

Type: *time.Time

A timestamp represented in epoch time.

InputDataLocationS3

Type: *string

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

LastUpdatedAt

Type: *time.Time

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

MLModelId

Type: *string

The ID assigned to the MLModel at creation.

MLModelType

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?".
Message

Type: *string

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

Name

Type: *string

A user-supplied name or description of the MLModel.

ScoreThreshold

Type: *float64

ScoreThresholdLastUpdatedAt

Type: *time.Time

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

SizeInBytes

Type: *int64

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

StartedAt

Type: *time.Time

A timestamp represented in epoch time.

Status

Type: *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.

TrainingDataSourceId

Type: *string

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

TrainingParameters

Type: map[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.

Method

GoString

func (s MLModel) GoString() string

GoString returns the string representation

SetAlgorithm

func (s *MLModel) SetAlgorithm(v string) *MLModel

SetAlgorithm sets the Algorithm field's value.

SetComputeTime

func (s *MLModel) SetComputeTime(v int64) *MLModel

SetComputeTime sets the ComputeTime field's value.

SetCreatedAt

func (s *MLModel) SetCreatedAt(v time.Time) *MLModel

SetCreatedAt sets the CreatedAt field's value.

SetCreatedByIamUser

func (s *MLModel) SetCreatedByIamUser(v string) *MLModel

SetCreatedByIamUser sets the CreatedByIamUser field's value.

SetEndpointInfo

func (s *MLModel) SetEndpointInfo(v *RealtimeEndpointInfo) *MLModel

SetEndpointInfo sets the EndpointInfo field's value.

SetFinishedAt

func (s *MLModel) SetFinishedAt(v time.Time) *MLModel

SetFinishedAt sets the FinishedAt field's value.

SetInputDataLocationS3

func (s *MLModel) SetInputDataLocationS3(v string) *MLModel

SetInputDataLocationS3 sets the InputDataLocationS3 field's value.

SetLastUpdatedAt

func (s *MLModel) SetLastUpdatedAt(v time.Time) *MLModel

SetLastUpdatedAt sets the LastUpdatedAt field's value.

SetMLModelId

func (s *MLModel) SetMLModelId(v string) *MLModel

SetMLModelId sets the MLModelId field's value.

SetMLModelType

func (s *MLModel) SetMLModelType(v string) *MLModel

SetMLModelType sets the MLModelType field's value.

SetMessage

func (s *MLModel) SetMessage(v string) *MLModel

SetMessage sets the Message field's value.

SetName

func (s *MLModel) SetName(v string) *MLModel

SetName sets the Name field's value.

SetScoreThreshold

func (s *MLModel) SetScoreThreshold(v float64) *MLModel

SetScoreThreshold sets the ScoreThreshold field's value.

SetScoreThresholdLastUpdatedAt

func (s *MLModel) SetScoreThresholdLastUpdatedAt(v time.Time) *MLModel

SetScoreThresholdLastUpdatedAt sets the ScoreThresholdLastUpdatedAt field's value.

SetSizeInBytes

func (s *MLModel) SetSizeInBytes(v int64) *MLModel

SetSizeInBytes sets the SizeInBytes field's value.

SetStartedAt

func (s *MLModel) SetStartedAt(v time.Time) *MLModel

SetStartedAt sets the StartedAt field's value.

SetStatus

func (s *MLModel) SetStatus(v string) *MLModel

SetStatus sets the Status field's value.

SetTrainingDataSourceId

func (s *MLModel) SetTrainingDataSourceId(v string) *MLModel

SetTrainingDataSourceId sets the TrainingDataSourceId field's value.

SetTrainingParameters

func (s *MLModel) SetTrainingParameters(v map[string]*string) *MLModel

SetTrainingParameters sets the TrainingParameters field's value.

String

func (s MLModel) String() string

String returns the string representation

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