Struct RankingMetrics 

#[non_exhaustive]
pub struct RankingMetrics {
    pub mean_average_precision: Option<DoubleValue>,
    pub mean_squared_error: Option<DoubleValue>,
    pub normalized_discounted_cumulative_gain: Option<DoubleValue>,
    pub average_rank: Option<DoubleValue>,
    /* private fields */
}

Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

mean_average_precision: Option<DoubleValue>

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

mean_squared_error: Option<DoubleValue>

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.

normalized_discounted_cumulative_gain: Option<DoubleValue>

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.

average_rank: Option<DoubleValue>

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

Implementations

impl RankingMetrics

pub fn new() -> Self

Creates a new default instance.

pub fn set_mean_average_precision<T>(self, v: T) -> Self

where T: Into<DoubleValue>,

Sets the value of mean_average_precision.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_mean_average_precision(DoubleValue::default()/* use setters */);

pub fn set_or_clear_mean_average_precision<T>(self, v: Option<T>) -> Self

where T: Into<DoubleValue>,

Sets or clears the value of mean_average_precision.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_or_clear_mean_average_precision(Some(DoubleValue::default()/* use setters */));
let x = RankingMetrics::new().set_or_clear_mean_average_precision(None::<DoubleValue>);

pub fn set_mean_squared_error<T>(self, v: T) -> Self

where T: Into<DoubleValue>,

Sets the value of mean_squared_error.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_mean_squared_error(DoubleValue::default()/* use setters */);

pub fn set_or_clear_mean_squared_error<T>(self, v: Option<T>) -> Self

where T: Into<DoubleValue>,

Sets or clears the value of mean_squared_error.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_or_clear_mean_squared_error(Some(DoubleValue::default()/* use setters */));
let x = RankingMetrics::new().set_or_clear_mean_squared_error(None::<DoubleValue>);

pub fn set_normalized_discounted_cumulative_gain<T>(self, v: T) -> Self

where T: Into<DoubleValue>,

Sets the value of normalized_discounted_cumulative_gain.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_normalized_discounted_cumulative_gain(DoubleValue::default()/* use setters */);

pub fn set_or_clear_normalized_discounted_cumulative_gain<T>( self, v: Option<T>, ) -> Self

where T: Into<DoubleValue>,

Sets or clears the value of normalized_discounted_cumulative_gain.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_or_clear_normalized_discounted_cumulative_gain(Some(DoubleValue::default()/* use setters */));
let x = RankingMetrics::new().set_or_clear_normalized_discounted_cumulative_gain(None::<DoubleValue>);

pub fn set_average_rank<T>(self, v: T) -> Self

where T: Into<DoubleValue>,

Sets the value of average_rank.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_average_rank(DoubleValue::default()/* use setters */);

pub fn set_or_clear_average_rank<T>(self, v: Option<T>) -> Self

where T: Into<DoubleValue>,

Sets or clears the value of average_rank.

Example

use wkt::DoubleValue;
let x = RankingMetrics::new().set_or_clear_average_rank(Some(DoubleValue::default()/* use setters */));
let x = RankingMetrics::new().set_or_clear_average_rank(None::<DoubleValue>);

Trait Implementations

impl Clone for RankingMetrics

fn clone(&self) -> RankingMetrics

Returns a duplicate 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 Message for RankingMetrics

fn typename() -> &'static str

The typename of this message.

impl PartialEq for RankingMetrics

fn eq(&self, other: &RankingMetrics) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl StructuralPartialEq for RankingMetrics