CustomerProfiles / Client / update_recommender

update_recommender

CustomerProfiles.Client.update_recommender(**kwargs)

Updates the properties of an existing recommender, allowing you to modify its configuration and description.

See also: AWS API Documentation

Request Syntax

response = client.update_recommender(
    DomainName='string',
    RecommenderName='string',
    Description='string',
    RecommenderConfig={
        'EventsConfig': {
            'EventParametersList': [
                {
                    'EventType': 'string',
                    'EventValueThreshold': 123.0,
                    'EventWeight': 123.0
                },
            ]
        },
        'TrainingFrequency': 123,
        'InferenceConfig': {
            'MinProvisionedTPS': 123
        },
        'IncludedColumns': {
            'string': [
                'string',
            ]
        }
    }
)
Parameters:

  • DomainName (string) –

    [REQUIRED]

    The unique name of the domain.

  • RecommenderName (string) –

    [REQUIRED]

    The name of the recommender to update.

  • Description (string) – The new description to assign to the recommender.

  • RecommenderConfig (dict) –

    The new configuration settings to apply to the recommender, including updated parameters and settings that define its behavior.

    • EventsConfig (dict) –

      Configuration settings for how the recommender processes and uses events.

      • EventParametersList (list) – [REQUIRED]

        A list of event parameters configurations that specify how different event types should be handled.

        • (dict) –

          Configuration parameters for events in the personalization system.

          • EventType (string) – [REQUIRED]

            The type of event being tracked (e.g., ‘click’, ‘purchase’, ‘view’).

          • EventValueThreshold (float) –

            The minimum value threshold that an event must meet to be considered valid.

          • EventWeight (float) –

            The weight of the event type. A higher weight means higher importance of the event type for the created solution.

    • TrainingFrequency (integer) –

      How often the recommender should retrain its model with new data.

    • InferenceConfig (dict) –

      Configuration settings for how the recommender handles inference requests.

      • MinProvisionedTPS (integer) –

        The minimum provisioned transactions per second (TPS) that the recommender supports. The default value is 1. A high MinProvisionedTPS will increase your cost.

    • IncludedColumns (dict) –

      A map of dataset type to a list of column names to train on. The column names must be a subset of the columns defined in the recommender schema. If not specified, all columns in the schema are used for training. The following columns are always included and do not need to be specified: Item.Id, ItemList[].Id, EventTimestamp, EventType, and EventValue.

      • (string) –

        • (list) –

          • (string) –

Return type:

dict

Returns:

Response Syntax

{
    'RecommenderName': 'string'
}

Response Structure

  • (dict) –

    • RecommenderName (string) –

      The name of the recommender that was updated.

Exceptions