[ aws . personalize ]
Describes a solution. For more information on solutions, see CreateSolution .
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
describe-solution
--solution-arn <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--cli-auto-prompt <value>]
--solution-arn
(string)
The Amazon Resource Name (ARN) of the solution to describe.
--cli-input-json
| --cli-input-yaml
(string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton
. If other arguments are provided on the command line, those 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. This may not be specified along with --cli-input-yaml
.
--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
. Similarly, if provided yaml-input
it will print a sample input YAML that can be used with --cli-input-yaml
. If provided with the value output
, it validates the command inputs and returns a sample output JSON for that command.
--cli-auto-prompt
(boolean)
Automatically prompt for CLI input parameters.
See ‘aws help’ for descriptions of global parameters.
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 usesrecipeArn
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
andMinimize
.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
is40
.maxParallelTrainingJobs -> (string)
The maximum number of parallel training jobs when you create a solution version. The maximum value for
maxParallelTrainingJobs
is10
.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.