import { BaseEstimator, ClassifierBase } from '../base';
import { Params } from '../base/estimator';
interface ProbabilisticClassifier extends BaseEstimator {
    fit(X: number[][], y: number[]): void;
    predict(X: number[][]): number[];
    predictProba(X: number[][]): number[][];
}
export interface SelfTrainingClassifierProps {
    estimator: ProbabilisticClassifier;
    threshold?: number;
    criterion?: 'threshold' | 'kBest';
    kBest?: number;
    maxIter?: number;
}
export declare class SelfTrainingClassifier extends ClassifierBase {
    private estimator;
    private threshold;
    private criterion;
    private kBest;
    private maxIter;
    private fittedEstimator?;
    private transductionState;
    private labeledIterationState;
    private nIterState;
    private terminationConditionState;
    constructor(props: SelfTrainingClassifierProps);
    getParams(): Params;
    setParams(params: Params): this;
    fit(X: number[][], y: number[]): void;
    private fitted;
    predict(X: number[][]): number[];
    predictProba(X: number[][]): number[][];
    get transduction(): number[];
    get labeledIteration(): number[];
    get nIter(): number;
    get terminationCondition(): string;
}
export {};