/**
 * Information Retrieval evaluation metrics
 */
/**
 * Normalized Discounted Cumulative Gain.
 * Measures ranking quality with position-based discounting.
 *
 * @param predicted - Predicted ranking with relevance scores
 * @param groundTruth - Ideal ranking (sorted by true relevance)
 * @param k - Cutoff position (default: all items)
 * @returns NDCG@k ∈ [0, 1], where 1 = perfect ranking
 */
export declare const ndcg: (predicted: Array<{
    id: string;
    relevance: number;
}>, groundTruth: Array<{
    id: string;
    relevance: number;
}>, k?: number) => number;
/**
 * Mean Average Precision.
 * Average of precision at each relevant item position.
 *
 * @param predicted - Predicted ranking (item IDs)
 * @param relevantItems - Set of relevant item IDs
 * @returns MAP ∈ [0, 1]
 */
export declare const meanAveragePrecision: (predicted: string[], relevantItems: Set<string>) => number;
/**
 * Mean Reciprocal Rank.
 * Reciprocal of rank of first relevant item.
 *
 * @param predicted - Predicted ranking (item IDs)
 * @param relevantItems - Set of relevant item IDs
 * @returns MRR ∈ [0, 1]
 */
export declare const meanReciprocalRank: (predicted: string[], relevantItems: Set<string>) => number;
/**
 * Precision at K.
 * Fraction of top-K items that are relevant.
 *
 * @param predicted - Predicted ranking (item IDs)
 * @param relevantItems - Set of relevant item IDs
 * @param k - Cutoff position
 * @returns P@K ∈ [0, 1]
 */
export declare const precisionAtK: (predicted: string[], relevantItems: Set<string>, k: number) => number;
/**
 * Recall at K.
 * Fraction of relevant items in top-K.
 *
 * @param predicted - Predicted ranking (item IDs)
 * @param relevantItems - Set of relevant item IDs
 * @param k - Cutoff position
 * @returns R@K ∈ [0, 1]
 */
export declare const recallAtK: (predicted: string[], relevantItems: Set<string>, k: number) => number;
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