RankingMetrics class
Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
Constructors
- RankingMetrics({double? averageRank, double? meanAveragePrecision, double? meanSquaredError, double? normalizedDiscountedCumulativeGain})
- RankingMetrics.fromJson(Map json_)
Properties
- averageRank ↔ double?
-
Determines the goodness of a ranking by computing the percentile rank from
the predicted confidence and dividing it by the original rank.
getter/setter pair
- hashCode → int
-
The hash code for this object.
no setterinherited
- meanAveragePrecision ↔ double?
-
Calculates a precision per user for all the items by ranking them and then
averages all the precisions across all the users.
getter/setter pair
- meanSquaredError ↔ double?
-
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.
getter/setter pair
- normalizedDiscountedCumulativeGain ↔ double?
-
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.
getter/setter pair
- runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
Methods
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
toJson(
) → Map< String, dynamic> -
toString(
) → String -
A string representation of this object.
inherited
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited