/**
*  @license
* Copyright 2021, JsData. All rights reserved.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.

* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* ==========================================================================
*/
import { Scikit1D, Tensor1D } from '../types';
import { Serialize } from '../simpleSerializer';
/**
 * Encode target labels with value between 0 and n_classes-1.
 * @example
 * ```js
 *  import { LabelEncoder } from 'scikitjs'
 *
 *  const sf = [1, 2, 2, 'boy', 'git', 'git']
    const scaler = new LabelEncoder()
    scaler.fit(sf)
    console.log(scaler.classes) // [1, 2, "boy", "git"]
    scaler.transform([2, 2, "boy"]) // [1, 1, 2]
 * ```
 */
export declare class LabelEncoder extends Serialize {
    /** Unique classes that we see in this single array of data */
    classes: Array<string | number | boolean>;
    /** Useful for pipelines and column transformers to have a default name for transforms */
    name: string;
    tf: any;
    constructor();
    convertTo1DArray(X: Scikit1D): Iterable<string | number | boolean>;
    classesToMapping(classes: Array<string | number | boolean>): Map<string | number | boolean, number>;
    /**
     * Maps values to unique integer labels between 0 and n_classes-1.
     * @example
     * ```js
     * const encoder = new LabelEncoder()
     * encoder.fit(["a", "b", "c", "d"])
     * ```
     */
    fit(X: Scikit1D): LabelEncoder;
    /**
     * Encode labels with value between 0 and n_classes-1.
     * @example
     * ```js
     * const encoder = new LabelEncoder()
     * encoder.fit(["a", "b", "c", "d"])
     * console.log(encoder.transform(["a", "b", "c", "d"]))
     * // [0, 1, 2, 3]
     * ```
     */
    transform(X: Scikit1D): Tensor1D;
    fitTransform(X: Scikit1D): Tensor1D;
    /**
     * Inverse transform values back to original values.
     * @example
     * ```js
     * const encoder = new LabelEncoder()
     * encoder.fit(["a", "b", "c", "d"])
     * console.log(encoder.inverseTransform([0, 1, 2, 3]))
     * // ["a", "b", "c", "d"]
     * ```
     */
    inverseTransform(X: Scikit1D): any[];
}