import { RegressorBase } from '../base';
import { Params } from '../base/estimator';
import { DecisionTreeRegressor } from '../tree/decisionTreeRegressor';
export interface AdaBoostRegressorProps {
    estimator?: DecisionTreeRegressor;
    n_estimators?: number;
    nEstimators?: number;
    learning_rate?: number;
    learningRate?: number;
    randomState?: number;
    random_state?: number;
}
/**
 * AdaBoost.R2 (Drucker, 1997), matching sklearn's AdaBoostRegressor with
 * linear loss: weighted resampling per round, weighted-median prediction.
 */
export declare class AdaBoostRegressor extends RegressorBase {
    private estimator;
    private n_estimators;
    private learning_rate;
    private randomState?;
    private estimators;
    private estimator_weights;
    constructor(props?: AdaBoostRegressorProps);
    getParams(): Params;
    fit(X: number[][], y: number[]): void;
    predict(X: number[][]): number[];
    get featureImportances(): number[];
}