import { TransformerBase } from '../base';
import { Params } from '../base/estimator';
export type KernelPCAKernel = 'linear' | 'poly' | 'rbf' | 'sigmoid' | 'cosine';
export interface KernelPCAProps {
    nComponents?: number | null;
    kernel?: KernelPCAKernel;
    gamma?: number;
    degree?: number;
    coef0?: number;
    alpha?: number;
    fitInverseTransform?: boolean;
    randomState?: number;
}
export declare class KernelPCA extends TransformerBase {
    private nComponents;
    private kernel;
    private gamma?;
    private degree;
    private coef0;
    private alpha;
    private fitInverseTransform;
    private randomState?;
    private resolvedGamma;
    private fitX;
    private eigenvaluesState;
    private eigenvectorsState;
    private kernelColumnMeans;
    private kernelTotalMean;
    private transformedFit;
    private inverseDual;
    constructor(props?: KernelPCAProps);
    getParams(): Params;
    private pair;
    private matrix;
    fit(X: number[][]): void;
    transform(X: number[][]): number[][];
    fitTransform(X: number[][]): number[][];
    inverseTransform(X: number[][]): number[][];
    get eigenvalues(): number[];
    get eigenvectors(): number[][];
}