Class RankingMetrics
Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
Inheritance
Implements
Inherited Members
Namespace: Google.Apis.Bigquery.v2.Data
Assembly: Google.Apis.Bigquery.v2.dll
Syntax
public class RankingMetrics : IDirectResponseSchema
Properties
AverageRank
Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
Declaration
[JsonProperty("averageRank")]
public virtual double? AverageRank { get; set; }
Property Value
Type | Description |
---|---|
System.Nullable<System.Double> |
ETag
The ETag of the item.
Declaration
public virtual string ETag { get; set; }
Property Value
Type | Description |
---|---|
System.String |
MeanAveragePrecision
Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
Declaration
[JsonProperty("meanAveragePrecision")]
public virtual double? MeanAveragePrecision { get; set; }
Property Value
Type | Description |
---|---|
System.Nullable<System.Double> |
MeanSquaredError
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.
Declaration
[JsonProperty("meanSquaredError")]
public virtual double? MeanSquaredError { get; set; }
Property Value
Type | Description |
---|---|
System.Nullable<System.Double> |
NormalizedDiscountedCumulativeGain
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.
Declaration
[JsonProperty("normalizedDiscountedCumulativeGain")]
public virtual double? NormalizedDiscountedCumulativeGain { get; set; }
Property Value
Type | Description |
---|---|
System.Nullable<System.Double> |