/*
* 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 Predictor = require('../Predictor')();
var gKernelP = kernelP;
/**
* @classdesc
* [Decision tree]{@link http://en.wikipedia.org/wiki/Decision_tree_learning} learning algorithm
* for regression.
* It supports both continuous and categorical features.
* @class
* @extends module:eclairjs/ml.Predictor
* @memberof module:eclairjs/ml/regression
* @param {string} [uid]
*/
function DecisionTreeRegressor() {
Utils.handleConstructor(this, arguments, gKernelP);
}
DecisionTreeRegressor.prototype = Object.create(Predictor.prototype);
DecisionTreeRegressor.prototype.constructor = DecisionTreeRegressor;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {Promise.<string>}
*/
DecisionTreeRegressor.prototype.uid = function () {
var args = {
target: this,
method: 'uid',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setMaxDepth = function(value) {
var args = {
target: this,
method: 'setMaxDepth',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setMaxBins = function(value) {
var args = {
target: this,
method: 'setMaxBins',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setMinInstancesPerNode = function(value) {
var args = {
target: this,
method: 'setMinInstancesPerNode',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setMinInfoGain = function(value) {
var args = {
target: this,
method: 'setMinInfoGain',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setMaxMemoryInMB = function(value) {
var args = {
target: this,
method: 'setMaxMemoryInMB',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {boolean} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setCacheNodeIds = function(value) {
var args = {
target: this,
method: 'setCacheNodeIds',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setCheckpointInterval = function(value) {
var args = {
target: this,
method: 'setCheckpointInterval',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {string} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setImpurity = function(value) {
var args = {
target: this,
method: 'setImpurity',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.setSeed = function(value) {
var args = {
target: this,
method: 'setSeed',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/regression.DecisionTreeRegressor}
*/
DecisionTreeRegressor.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
/**
* @param {string} value
* @returns {type}
*/
DecisionTreeRegressor.prototype.setVarianceCol = function(value) {
var args ={
target: this,
method: 'setVarianceCol',
args: Utils.wrapArguments(arguments),
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
//
// static methods
//
/**
* @param {string} path
* @returns {DecisionTreeRegressor}
*/
DecisionTreeRegressor.load = function(path) {
var args ={
target: DecisionTreeRegressor,
method: 'load',
args: Utils.wrapArguments(arguments),
static: true,
returnType: DecisionTreeRegressor
};
return Utils.generate(args);
};
DecisionTreeRegressor.moduleLocation = '/ml/regression/DecisionTreeRegressor';
return DecisionTreeRegressor;
})();
};