View Source GoogleApi.BigQuery.V2.Model.RankingMetrics (google_api_big_query v0.79.0)
Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
Attributes
-
averageRank
(type:float()
, default:nil
) - Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank. -
meanAveragePrecision
(type:float()
, default:nil
) - Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users. -
meanSquaredError
(type:float()
, default:nil
) - Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not. -
normalizedDiscountedCumulativeGain
(type:float()
, default:nil
) - A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
Summary
Functions
Unwrap a decoded JSON object into its complex fields.
Types
Functions
Unwrap a decoded JSON object into its complex fields.