@jsmlt/jsmlt/distribution/preprocessing/labelencoder.js

JavaScript Machine Learning

"use strict";

Object.defineProperty(exports, "__esModule", {
  value: true
});
exports["default"] = void 0;

function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }

function _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }

function _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }

/**
 * Encoder of categorical values to integers. For k different values, encoding yields integer
 * numbers from 0 to k-1 (inclusive).
 *
 * @example
 * // List of raw input values
 * var y = ['Car', 'Bike', 'Bike', 'Car', 'Duck', 'Bike'];
 *
 * // Create encoder
 * var encoder = new LabelEncoder();
 *
 * // Encode input values, encoding the values to integers
 * var yEncoded = encoder.encode(y);
 * console.log(yEncoded); // [0, 1, 1, 0, 2, 0]
 *
 * // Decode the encoded values, and see that they match the original input values
 * console.log(encoder.decode(yEncoded)); // ['Car', 'Bike', 'Bike', 'Car', 'Duck', 'Bike']
 */
var LabelEncoder =
/*#__PURE__*/
function () {
  /**
   * Initialize object properties.
   */
  function LabelEncoder() {
    _classCallCheck(this, LabelEncoder);

    /**
     * Dictionary mapping class labels to class indices.
     *
     * @type {Object.<string, number>}
     */
    this.labelsClassIndex = {};
    /**
     * Array of class labels for class indices
     *
     * @type {Array.<string>}
     */

    this.classIndicesLabel = [];
    /**
     * Number of unique class labels
     *
     * @type {number}
     */

    this.numLabels = 0;
  }
  /**
   * Encode a set of labels or a single label.
   *
   * @param {mixed|Array.<mixed>} labels - Single label or list of labels. Each label should support
   *   the toString() method
   * @return {number|Array.<number>} Single encoded label or list of encoded labels (i.e., integers
   *   associated with the input labels)
   */


  _createClass(LabelEncoder, [{
    key: "encode",
    value: function encode(labels) {
      var _this = this;

      // In case multiple labels are passed, encode them one-by-one
      if (Array.isArray(labels)) {
        return labels.map(function (label) {
          return _this.encode(label);
        });
      } // In case a single label is passed, encode it


      var labelString = labels.toString();

      if (typeof this.labelsClassIndex[labelString] === 'undefined') {
        this.labelsClassIndex[labelString] = this.numLabels;
        this.classIndicesLabel.push(labelString);
        this.numLabels += 1;
      }

      return this.labelsClassIndex[labelString];
    }
    /**
     * Decode a set of labels or a single label.
     *
     * @param {number|Array.<number>} encodedLabels - Single encoded label or list of encoded labels
     * @return {mixed|Array.<mixed>} Single decoded label or list of decoded labels
     */

  }, {
    key: "decode",
    value: function decode(encodedLabels) {
      var _this2 = this;

      // In case multiple labels are passed, decode them one-by-one
      if (Array.isArray(encodedLabels)) {
        return encodedLabels.map(function (label) {
          return _this2.decode(label);
        });
      } // In case a single label is passed, decode it


      return typeof this.classIndicesLabel[encodedLabels] === 'undefined' ? -1 : this.classIndicesLabel[encodedLabels];
    }
  }]);

  return LabelEncoder;
}();

exports["default"] = LabelEncoder;
module.exports = exports.default;