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[ aws . personalize ]

describe-solution

Description

Describes a solution. For more information on solutions, see CreateSolution .

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  describe-solution
--solution-arn <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--solution-arn (string)

The Amazon Resource Name (ARN) of the solution to describe.

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

solution -> (structure)

An object that describes the solution.

name -> (string)

The name of the solution.

solutionArn -> (string)

The ARN of the solution.

performHPO -> (boolean)

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false .

performAutoML -> (boolean)

When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration (recipeArn must not be specified). When false (the default), Amazon Personalize uses recipeArn for training.

recipeArn -> (string)

The ARN of the recipe used to create the solution.

datasetGroupArn -> (string)

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

eventType -> (string)

The event type (for example, 'click' or 'like') that is used for training the model.

solutionConfig -> (structure)

Describes the configuration properties for the solution.

eventValueThreshold -> (string)

Only events with a value greater than or equal to this threshold are used for training a model.

hpoConfig -> (structure)

Describes the properties for hyperparameter optimization (HPO).

hpoObjective -> (structure)

The metric to optimize during HPO.

type -> (string)

The type of the metric. Valid values are Maximize and Minimize .

metricName -> (string)

The name of the metric.

metricRegex -> (string)

A regular expression for finding the metric in the training job logs.

hpoResourceConfig -> (structure)

Describes the resource configuration for HPO.

maxNumberOfTrainingJobs -> (string)

The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40 .

maxParallelTrainingJobs -> (string)

The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10 .

algorithmHyperParameterRanges -> (structure)

The hyperparameters and their allowable ranges.

integerHyperParameterRanges -> (list)

The integer-valued hyperparameters and their ranges.

(structure)

Provides the name and range of an integer-valued hyperparameter.

name -> (string)

The name of the hyperparameter.

minValue -> (integer)

The minimum allowable value for the hyperparameter.

maxValue -> (integer)

The maximum allowable value for the hyperparameter.

continuousHyperParameterRanges -> (list)

The continuous hyperparameters and their ranges.

(structure)

Provides the name and range of a continuous hyperparameter.

name -> (string)

The name of the hyperparameter.

minValue -> (double)

The minimum allowable value for the hyperparameter.

maxValue -> (double)

The maximum allowable value for the hyperparameter.

categoricalHyperParameterRanges -> (list)

The categorical hyperparameters and their ranges.

(structure)

Provides the name and range of a categorical hyperparameter.

name -> (string)

The name of the hyperparameter.

values -> (list)

A list of the categories for the hyperparameter.

(string)

algorithmHyperParameters -> (map)

Lists the hyperparameter names and ranges.

key -> (string)

value -> (string)

featureTransformationParameters -> (map)

Lists the feature transformation parameters.

key -> (string)

value -> (string)

autoMLConfig -> (structure)

The AutoMLConfig object containing a list of recipes to search when AutoML is performed.

metricName -> (string)

The metric to optimize.

recipeList -> (list)

The list of candidate recipes.

(string)

autoMLResult -> (structure)

When performAutoML is true, specifies the best recipe found.

bestRecipeArn -> (string)

The Amazon Resource Name (ARN) of the best recipe.

status -> (string)

The status of the solution.

A solution can be in one of the following states:

  • CREATE PENDING CREATE IN_PROGRESS ACTIVE -or- CREATE FAILED
  • DELETE PENDING DELETE IN_PROGRESS

creationDateTime -> (timestamp)

The creation date and time (in Unix time) of the solution.

lastUpdatedDateTime -> (timestamp)

The date and time (in Unix time) that the solution was last updated.

latestSolutionVersion -> (structure)

Describes the latest version of the solution, including the status and the ARN.

solutionVersionArn -> (string)

The Amazon Resource Name (ARN) of the solution version.

status -> (string)

The status of the solution version.

A solution version can be in one of the following states:

  • CREATE PENDING CREATE IN_PROGRESS ACTIVE -or- CREATE FAILED

creationDateTime -> (timestamp)

The date and time (in Unix time) that this version of a solution was created.

lastUpdatedDateTime -> (timestamp)

The date and time (in Unix time) that the solution version was last updated.

failureReason -> (string)

If a solution version fails, the reason behind the failure.