/*
* 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.
*/
module.exports = function(kernelP) {
return (function() {
var Utils = require('../../utils.js');
var PredictionModel = require('../PredictionModel')();
var gKernelP = kernelP;
/**
* @classdesc
*
* [Gradient-Boosted Trees (GBTs)]{@link http://en.wikipedia.org/wiki/Gradient_boosting}
* model for regression.
* It supports both continuous and categorical features.
* @class
* @extends module:eclairjs/ml.PredictionModel
* @memberof module:eclairjs/ml/regression
* @oaram {string} uid
* @param {DecisionTreeRegressionModel[]} trees Decision trees in the ensemble.
* @param {float[]} treeWeights Weights for the decision trees in the ensemble.
*/
function GBTRegressionModel() {
Utils.handleConstructor(this, arguments, gKernelP);
}
GBTRegressionModel.prototype = Object.create(PredictionModel.prototype);
GBTRegressionModel.prototype.constructor = GBTRegressionModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {Promise.<string>}
*/
GBTRegressionModel.prototype.uid = function () {
var args = {
target: this,
method: 'uid',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* @returns {DecisionTreeRegressionModel[]}
*/
GBTRegressionModel.prototype.trees = function() {
throw "not implemented by ElairJS";
// var args ={
// target: this,
// method: 'trees',
// returnType: [DecisionTreeRegressionModel]
//
// };
//
// return Utils.generate(args);
};
/**
* @returns {Promise.<number[]>}
*/
GBTRegressionModel.prototype.treeWeights = function() {
var args = {
target: this,
method: 'treeWeights',
args: Utils.wrapArguments(arguments),
returnType: [Number]
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/regression.GBTRegressionModel}
*/
GBTRegressionModel.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: GBTRegressionModel
};
return Utils.generate(args);
};
/**
* @returns {Promise.<string>}
*/
GBTRegressionModel.prototype.toString = function() {
var args = {
target: this,
method: 'toString',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* @returns {MLWriter}
*/
GBTRegressionModel.prototype.write = function() {
var MLWriter = require('../../ml/util/MLWriter.js');
var args ={
target: this,
method: 'write',
returnType: MLWriter
};
return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {MLReader}
*/
GBTRegressionModel.read = function() {
var MLReader = require('../../ml/util/MLReader.js');
var args ={
target: GBTRegressionModel,
method: 'read',
static: true,
returnType: MLReader
};
return Utils.generate(args);
};
/**
* @param {string} path
* @returns {GBTRegressionModel}
*/
GBTRegressionModel.load = function(path) {
var args ={
target: GBTRegressionModel,
method: 'load',
args: Utils.wrapArguments(arguments),
static: true,
returnType: GBTRegressionModel
};
return Utils.generate(args);
};
GBTRegressionModel.moduleLocation = '/ml/regression/GBTRegressionModel';
return GBTRegressionModel;
})();
};