RecommenderConfig
Configuration settings that define the behavior and parameters of a recommender.
Contents
- EventsConfig
-
Configuration settings for how the recommender processes and uses events.
Type: EventsConfig object
Required: No
- IncludedColumns
-
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, andEventValue.Type: String to array of strings map
Map Entries: Maximum number of 2 items.
Array Members: Minimum number of 1 item. Maximum number of 100 items.
Length Constraints: Minimum length of 1. Maximum length of 1000.
Required: No
- InferenceConfig
-
Configuration settings for how the recommender handles inference requests.
Type: InferenceConfig object
Required: No
- TrainingFrequency
-
How often the recommender should retrain its model with new data.
Type: Integer
Valid Range: Minimum value of 1. Maximum value of 30.
Required: No
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
