Source: mllib/tree/model/GradientBoostedTreesModel.js

/*
 * Copyright 2016 IBM Corp.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * 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.
 */

var Utils = require('../../../utils.js');

var gKernelP;

/**
 * Represents a gradient boosted trees model.
 *
 * @param algo algorithm for the ensemble model, either Classification or Regression
 * @param trees tree ensembles
 * @param treeWeights tree ensemble weights
 * @classdesc
 * @class
 * @memberof module:eclairjs/mllib/tree/model
 */
function GradientBoostedTreesModel() {
  Utils.handleConstructor(this, arguments, gKernelP);
}

/**
 * @param {module:eclairjs.SparkContext} sc   Spark context used to save model data.
 * @param {string} path   Path specifying the directory in which to save this model.
 *              If the directory already exists, this method throws an exception.
 * @returns {Promise.<Void>} A Promise that resolves to nothing.
 */
GradientBoostedTreesModel.prototype.save = function(sc,path) {
  var args = {
    target: this,
    method: 'save',
    args: Utils.wrapArguments(arguments)
  };

  return Utils.generate(args);
};

/**
 * Method to compute error or loss for every iteration of gradient boosting.
 * @param {module:eclairjs/rdd.RDD} data  RDD of {@link LabeledPoint}
 * @param {module:eclairjs/mllib/tree/loss.Loss} loss  evaluation metric.
 *         containing the first i+1 trees
 * @returns {Promise.<number[]>}  an array with index i having the losses or errors for the ensemble
 */
GradientBoostedTreesModel.prototype.evaluateEachIteration = function(data,loss) {
  var args = {
    target: this,
    method: 'evaluateEachIteration',
    args: Utils.wrapArguments(arguments),
    returnType: Number
  };

  return Utils.generate(args);
};

//
// static methods
//

/**
 * @param {module:eclairjs.SparkContext} sc   Spark context used for loading model files.
 * @param {string} path   Path specifying the directory to which the model was saved.
 * @returns {GradientBoostedTreesModel}   Model instance
 */
GradientBoostedTreesModel.load = function(sc,path) {
  var args = {
    target: GradientBoostedTreesModel,
    method: 'load',
    args: Utils.wrapArguments(arguments),
    static: true,
    kernelP: gKernelP,
    returnType: GradientBoostedTreesModel
  };

  return Utils.generate(args);
};

GradientBoostedTreesModel.moduleLocation = '/mllib/tree/model/GradientBoostedTreesModel';

module.exports = function(kP) {
  if (kP) gKernelP = kP;

  return GradientBoostedTreesModel;
};