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RecommenderConfig

Source code in docs_src/capo_personalize/types/recommender_config.py
class RecommenderConfig(TypedDict, closed=True):
    item_exploration_config: NotRequired[
        "capo_personalize.types.hyper_parameters.HyperParameters"
    ]
    """<p>Specifies the exploration configuration hyperparameters, including <code>explorationWeight</code> and <code>explorationItemAgeCutOff</code>, you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide <code>itemExplorationConfig</code> data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).</p>"""
    min_recommendation_requests_per_second: NotRequired[
        "capo_personalize.types.transactions_per_second.TransactionsPerSecond"
    ]
    """<p>Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support. A high <code>minRecommendationRequestsPerSecond</code> will increase your bill. We recommend starting with 1 for <code>minRecommendationRequestsPerSecond</code> (the default). Track your usage using Amazon CloudWatch metrics, and increase the <code>minRecommendationRequestsPerSecond</code> as necessary.</p>"""
    training_data_config: NotRequired[
        "capo_personalize.types.training_data_config.TrainingDataConfig"
    ]
    """<p> Specifies the training data configuration to use when creating a domain recommender. </p>"""
    enable_metadata_with_recommendations: NotRequired[
        "capo_personalize.types.boolean.Boolean"
    ]
    """<p>Whether metadata with recommendations is enabled for the recommender. If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. For information about enabling metadata for a recommender, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/creating-recommenders.html#create-recommender-return-metadata">Enabling metadata in recommendations for a recommender</a>.</p> <p> If you enable metadata in recommendations, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>. </p>"""

enable_metadata_with_recommendations instance-attribute

enable_metadata_with_recommendations: NotRequired[Boolean]

Whether metadata with recommendations is enabled for the recommender. If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. For information about enabling metadata for a recommender, see Enabling metadata in recommendations for a recommender.

If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.

item_exploration_config instance-attribute

item_exploration_config: NotRequired[HyperParameters]

Specifies the exploration configuration hyperparameters, including explorationWeight and explorationItemAgeCutOff, you want to use to configure the amount of item exploration Amazon Personalize uses when recommending items. Provide itemExplorationConfig data only if your recommenders generate personalized recommendations for a user (not popular items or similar items).

min_recommendation_requests_per_second instance-attribute

min_recommendation_requests_per_second: NotRequired[TransactionsPerSecond]

Specifies the requested minimum provisioned recommendation requests per second that Amazon Personalize will support. A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics, and increase the minRecommendationRequestsPerSecond as necessary.

training_data_config instance-attribute

training_data_config: NotRequired[TrainingDataConfig]

Specifies the training data configuration to use when creating a domain recommender.