/** Shared validation and small numeric helpers for discriminant analysis. */
export declare function validateXy(X: number[][], y: number[], name: string): void;
export declare function validatePredictInput(X: number[][], nFeatures: number, name: string): void;
export declare function sortedUniqueLabels(y: number[]): number[];
/**
 * Resolve class priors: from explicit user priors (validated, normalized to
 * sum to 1 like sklearn) or from class frequencies.
 */
export declare function resolvePriors(priors: number[] | undefined, counts: number[], nSamples: number, name: string): number[];
/** Row-wise softmax with max-subtraction for numerical stability. */
export declare function softmaxRows(scores: number[][]): number[][];
export declare function argmaxRow(row: number[]): number;
/** Per-class means; `classIdx[i]` maps sample i to its class index. */
export declare function classMeans(X: number[][], classIdx: number[], nClasses: number): number[][];