AWS SDK for Go (PILOT)
API Reference

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GetMLModelOutput

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

type GetMLModelOutput struct { 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"` LogUri *string `type:"string"` MLModelId *string `min:"1" type:"string"` MLModelType *string `type:"string" enum:"MLModelType"` Message *string `type:"string"` Name *string `type:"string"` Recipe *string `type:"string"` Schema *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, and provides detailed information about a MLModel.

ComputeTime

Type: *int64

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.

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

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.

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.

LogUri

Type: *string

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

MLModelId

Type: *string

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

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 an e-commerce website?"

  • 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.

Recipe

Type: *string

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.

NoteThis parameter is provided as part of the verbose format.

Schema

Type: *string

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

NoteThis parameter is provided as part of the verbose format.

ScoreThreshold

Type: *float64

The scoring threshold is used in binary classification MLModelmodels. 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

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

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

Status

Type: *string

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.

TrainingDataSourceId

Type: *string

The ID of the training DataSource.

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 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.

Method

GoString

func (s GetMLModelOutput) GoString() string

GoString returns the string representation

SetComputeTime

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

SetComputeTime sets the ComputeTime field's value.

SetCreatedAt

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

SetCreatedAt sets the CreatedAt field's value.

SetCreatedByIamUser

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

SetCreatedByIamUser sets the CreatedByIamUser field's value.

SetEndpointInfo

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

SetEndpointInfo sets the EndpointInfo field's value.

SetFinishedAt

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

SetFinishedAt sets the FinishedAt field's value.

SetInputDataLocationS3

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

SetInputDataLocationS3 sets the InputDataLocationS3 field's value.

SetLastUpdatedAt

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

SetLastUpdatedAt sets the LastUpdatedAt field's value.

SetLogUri

func (s *GetMLModelOutput) SetLogUri(v string) *GetMLModelOutput

SetLogUri sets the LogUri field's value.

SetMLModelId

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

SetMLModelId sets the MLModelId field's value.

SetMLModelType

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

SetMLModelType sets the MLModelType field's value.

SetMessage

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

SetMessage sets the Message field's value.

SetName

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

SetName sets the Name field's value.

SetRecipe

func (s *GetMLModelOutput) SetRecipe(v string) *GetMLModelOutput

SetRecipe sets the Recipe field's value.

SetSchema

func (s *GetMLModelOutput) SetSchema(v string) *GetMLModelOutput

SetSchema sets the Schema field's value.

SetScoreThreshold

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

SetScoreThreshold sets the ScoreThreshold field's value.

SetScoreThresholdLastUpdatedAt

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

SetScoreThresholdLastUpdatedAt sets the ScoreThresholdLastUpdatedAt field's value.

SetSizeInBytes

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

SetSizeInBytes sets the SizeInBytes field's value.

SetStartedAt

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

SetStartedAt sets the StartedAt field's value.

SetStatus

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

SetStatus sets the Status field's value.

SetTrainingDataSourceId

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

SetTrainingDataSourceId sets the TrainingDataSourceId field's value.

SetTrainingParameters

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

SetTrainingParameters sets the TrainingParameters field's value.

String

func (s GetMLModelOutput) String() string

String returns the string representation

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