Struct gcp_bigquery_client::model::ranking_metrics::RankingMetrics

pub struct RankingMetrics {
    pub mean_average_precision: Option<f64>,
    pub normalized_discounted_cumulative_gain: Option<f64>,
    pub mean_squared_error: Option<f64>,
    pub average_rank: Option<f64>,
}

Fields

mean_average_precision: Option<f64>

Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.

normalized_discounted_cumulative_gain: Option<f64>

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.

mean_squared_error: Option<f64>

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.

average_rank: Option<f64>

Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.

Trait Implementations

impl Clone for RankingMetrics

fn clone(&self) -> RankingMetrics

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RankingMetrics

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for RankingMetrics

fn default() -> RankingMetrics

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for RankingMetrics

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl Serialize for RankingMetrics

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.