import { ClassifierBase } from '../base';
import { Params } from '../base/estimator';
import { type NumericMatrix } from '../data';
export interface GaussianNBProps {
    priors?: number[] | null;
    varSmoothing?: number;
}
export declare class GaussianNB extends ClassifierBase {
    readonly acceptedInputKinds: readonly ["dense", "csr"];
    private priors;
    private varSmoothing;
    private classes;
    private theta;
    private variances;
    private classPrior;
    private epsilon;
    private fitted;
    constructor(props?: GaussianNBProps);
    getParams(): Params;
    fit(X: NumericMatrix, y: number[]): void;
    private jointLogLikelihood;
    predict(X: NumericMatrix): number[];
    /** Class posteriors, columns ordered by sorted `classes` (sklearn's predict_proba). */
    predictProba(X: NumericMatrix): number[][];
    getClasses(): number[];
}