import { BaseEstimator, Params } from '../base/estimator';
export type ColumnTransformerEntry = [
    name: string,
    transformer: BaseEstimator | 'passthrough' | 'drop',
    columns: number[]
];
export interface ColumnTransformerProps {
    transformers: ColumnTransformerEntry[];
    /** What to do with columns not claimed by any transformer. Default 'drop'. */
    remainder?: 'drop' | 'passthrough';
}
/**
 * Applies different transformers to different column subsets and
 * concatenates the results (transformer outputs in declaration order,
 * remainder-passthrough columns last), like sklearn's ColumnTransformer.
 */
export declare class ColumnTransformer extends BaseEstimator {
    private transformers;
    private remainder;
    private remainderColumns;
    private nFeaturesIn;
    private fitted;
    constructor(props: ColumnTransformerProps);
    getParams(): Params;
    /** Supports nested `name__param` addressing like Pipeline. */
    setParams(params: Params): this;
    getTransformer(name: string): BaseEstimator | 'passthrough' | 'drop';
    fit(X: number[][], y?: number[]): void;
    transform(X: number[][]): number[][];
    fitTransform(X: number[][], y?: number[]): number[][];
}