import { Model } from "../Model";
import { Instance } from "../../Instance/Instance";
import { DecisionTree } from "../DecisionTree/DecisionTree";
export declare abstract class TreeEnsembleModel extends Model {
    protected forest: Array<DecisionTree>;
    /**
     * A constructor which sets the {@link Array} of {@link DecisionTree} with given input.
     *
     * @param forest An {@link Array} of {@link DecisionTree}.
     */
    constructor1(forest: Array<DecisionTree>): void;
    /**
     * Loads a tree ensemble model such as Random Forest model or Bagging model from an input model file.
     * @param fileName Model file name.
     */
    constructor2(fileName: string): void;
    /**
     * The predict method takes an {@link Instance} as an input and loops through the {@link ArrayList} of {@link DecisionTree}s.
     * Makes prediction for the items of that ArrayList and returns the maximum item of that ArrayList.
     *
     * @param instance Instance to make prediction.
     * @return The maximum prediction of a given Instance.
     */
    predict(instance: Instance): string;
    /**
     * Calculates the posterior probability distribution for the given instance according to ensemble tree model.
     * @param instance Instance for which posterior probability distribution is calculated.
     * @return Posterior probability distribution for the given instance.
     */
    predictProbability(instance: Instance): Map<string, number>;
    saveTxt(fileName: string): void;
}