Source: eclairjs/mllib/tree/model/GradientBoostedTreesModel.js

  1. /**
  2.  * Created by billreed on 4/11/16.
  3.  *//*
  4.  * Copyright 2016 IBM Corp.
  5.  *
  6.  * Licensed under the Apache License, Version 2.0 (the "License");
  7.  * you may not use this file except in compliance with the License.
  8.  * You may obtain a copy of the License at
  9.  *
  10.  *      http://www.apache.org/licenses/LICENSE-2.0
  11.  *
  12.  * Unless required by applicable law or agreed to in writing, software
  13.  * distributed under the License is distributed on an "AS IS" BASIS,
  14.  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  15.  * See the License for the specific language governing permissions and
  16.  * limitations under the License.
  17.  */
  19. (function () {
  20.     var JavaWrapper = require(EclairJS_Globals.NAMESPACE + '/JavaWrapper');
  21.     var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
  22.     var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
  23.     /**
  24.      * Represents a gradient boosted trees model.
  25.      *
  26.      * @param algo algorithm for the ensemble model, either Classification or Regression
  27.      * @param trees tree ensembles
  28.      * @param treeWeights tree ensemble weights
  29.      * @classdesc
  30.      */
  32.     /**
  33.      * @param {Algo} algo
  34.      * @param {module:eclairjs/mllib/tree/model.DecisionTreeModel[]} trees
  35.      * @param {number[]} treeWeights
  36.      * @returns {??}
  37.      *  @class
  38.      *  @memberof module:eclairjs/mllib/tree/model
  39.      */
  40.     var GradientBoostedTreesModel = function (algo, trees, treeWeights) {
  41.         this.logger = Logger.getLogger("GradientBoostedTreesModel_js");
  42.         var jvmObject;
  43.         if (arguments[0] instanceof org.apache.spark.mllib.tree.model.GradientBoostedTreesModel) {
  44.             jvmObject = arguments[0];
  45.         } else {
  46.             jvmObject = new org.apache.spark.mllib.tree.model.GradientBoostedTreesModel(Utils.unwrapObject(arguments[0]),
  47.                 Utils.unwrapObject(trees),
  48.                 treeWeights
  49.             );
  50.         }
  51.         JavaWrapper.call(this, jvmObject);
  53.     };
  55.     GradientBoostedTreesModel.prototype = Object.create(JavaWrapper.prototype);
  57.     GradientBoostedTreesModel.prototype.constructor = GradientBoostedTreesModel;
  60.     /**
  61.      * @param {module:eclairjs.SparkContext} sc   Spark context used to save model data.
  62.      * @param {string} path   Path specifying the directory in which to save this model.
  63.      *              If the directory already exists, this method throws an exception.
  64.      */
  65.     GradientBoostedTreesModel.prototype.save = function (sc, path) {
  66.         var sc_uw = Utils.unwrapObject(sc);
  67.         this.getJavaObject().save(sc_uw.sc(), path);
  68.     };
  71.     /**
  72.      * Method to compute error or loss for every iteration of gradient boosting.
  73.      * @param {module:eclairjs.RDD} data  RDD of {@link LabeledPoint}
  74.      * @param {module:eclairjs/mllib/tree/loss.Loss} loss  evaluation metric.
  75.      *         containing the first i+1 trees
  76.      * @returns {number[]}  an array with index i having the losses or errors for the ensemble
  77.      */
  78.     GradientBoostedTreesModel.prototype.evaluateEachIteration = function (data, loss) {
  79.         throw "not implemented by ElairJS";
  80. //   var data_uw = Utils.unwrapObject(data);
  81. //   var loss_uw = Utils.unwrapObject(loss);
  82. //   return  this.getJavaObject().evaluateEachIteration(data_uw,loss_uw);
  83.     };
  85.     GradientBoostedTreesModel.prototype.predict = function (features) {
  86.         var features_uw = Utils.unwrapObject(features);
  87.         return this.getJavaObject().predict(features_uw);
  88.     };
  90.     /**
  91.      * Print the full model to a string.
  92.      * @returns {string}
  93.      */
  94.     GradientBoostedTreesModel.prototype.toDebugString = function () {
  95.         return this.getJavaObject().toDebugString();
  96.     };
  98.     /**
  99.      * Print a summary of the model.
  100.      * @returns {string}
  101.      */
  102.     GradientBoostedTreesModel.prototype.toString = function () {
  103.         return this.getJavaObject().toString();
  104.     };
  106. //
  107. // static methods
  108. //
  110.     /**
  111.      * @param {module:eclairjs.SparkContext} sc   Spark context used for loading model files.
  112.      * @param {string} path   Path specifying the directory to which the model was saved.
  113.      * @returns {module:eclairjs/mllib/tree/model.GradientBoostedTreesModel}   Model instance
  114.      */
  115.     GradientBoostedTreesModel.load = function (sc, path) {
  116.         var sc_uw = Utils.unwrapObject(sc);
  117.         var javaObject = org.apache.spark.mllib.tree.model.GradientBoostedTreesModel.load(sc_uw.sc(), path);
  118.         return new GradientBoostedTreesModel(javaObject);
  119.     };
  121.     module.exports = GradientBoostedTreesModel;
  123. })();