Struct NormalizedDiscountedCumulativeGain 

pub struct NormalizedDiscountedCumulativeGain {
    pub k: usize,
}

Normalized Discounted Cumulative Gain (NDCG) metric for ranking.

NDCG measures the quality of ranking by comparing the predicted order with the ideal order. It accounts for position: items ranked higher contribute more to the score.

Formula

DCG@k = Σᵢ₌₁ᵏ (2^relᵢ - 1) / log₂(i + 1) NDCG@k = DCG@k / IDCG@k

where IDCG is the DCG of the ideal ranking.

Use Cases

• Recommendation systems
• Search engine ranking
• Information retrieval
• Learning to rank

Reference: Järvelin & Kekäläinen “Cumulated gain-based evaluation of IR techniques” (ACM TOIS 2002)

Fields

k: usize

Number of top results to consider (k).

Implementations

impl NormalizedDiscountedCumulativeGain

pub fn new(k: usize) -> Self

Create NDCG metric with custom k value.

Arguments

• k - Number of top results to consider

Trait Implementations

impl Clone for NormalizedDiscountedCumulativeGain

fn clone(&self) -> NormalizedDiscountedCumulativeGain

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NormalizedDiscountedCumulativeGain

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

Formats the value using the given formatter.

impl Default for NormalizedDiscountedCumulativeGain

fn default() -> Self

Returns the “default value” for a type.

impl Metric for NormalizedDiscountedCumulativeGain

fn compute( &self, predictions: &ArrayView<'_, f64, Ix2>, targets: &ArrayView<'_, f64, Ix2>, ) -> TrainResult<f64>

Compute metric value.

fn name(&self) -> &str

Get metric name.

fn reset(&mut self)

Reset metric state (for stateful metrics).