google_api_big_query v0.35.0 GoogleApi.BigQuery.V2.Model.RankingMetrics View Source
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.
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Functions
Unwrap a decoded JSON object into its complex fields.
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Link to this section Functions
Unwrap a decoded JSON object into its complex fields.