/*
* 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.
*/
(function () {
var PredictionModel = require(EclairJS_Globals.NAMESPACE + '/ml/PredictionModel');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* @classdesc
* [Gradient-Boosted Trees (GBTs)]{@link http://en.wikipedia.org/wiki/Gradient_boosting}
* model for classification.
* It supports binary labels, as well as both continuous and categorical features.
* Note: Multiclass labels are not currently supported.
* @class
* @extends module:eclairjs/ml.PredictionModel
* @memberof module:eclairjs/ml/classification
* @param {string} uid
* @param {DecisionTreeRegressionModel[]} trees Decision trees in the ensemble.
* @param {float[]} treeWeights Weights for the decision trees in the ensemble.
*/
var GBTClassificationModel = function (uid, trees, treeWeights) {
this.logger = Logger.getLogger("ml_classification_GBTClassificationModel_js");
var jvmObject;
if (uid instanceof org.apache.spark.ml.classification.GBTClassificationModel) {
jvmObject = uid;
} else {
var tress_uw = Utils.unwrapObject(trees);
jvmObject = new org.apache.spark.ml.classification.GBTClassificationModel(uid, tress_uw, treeWeights);
}
PredictionModel.call(this, jvmObject);
};
GBTClassificationModel.prototype = Object.create(PredictionModel.prototype);
GBTClassificationModel.prototype.constructor = GBTClassificationModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {string}
*/
GBTClassificationModel.prototype.uid = function () {
return this.getJavaObject().uid();
};
/**
* @returns {DecisionTreeRegressionModel[]}
*/
GBTClassificationModel.prototype.trees = function () {
var javaObject = this.getJavaObject().trees();
return Utils.javaToJs(javaObject);
};
/**
* @returns {float[]}
*/
GBTClassificationModel.prototype.treeWeights = function () {
return this.getJavaObject().treeWeights();
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/classification.GBTClassificationModel}
*/
GBTClassificationModel.prototype.copy = function (extra) {
var extra_uw = Utils.unwrapObject(extra);
var javaObject = this.getJavaObject().copy(extra_uw);
return new GBTClassificationModel(javaObject);
};
/**
* @returns {string}
*/
GBTClassificationModel.prototype.toString = function () {
return this.getJavaObject().toString();
};
/**
* @returns {string}
*/
GBTClassificationModel.prototype.toDebugString = function () {
return this.getJavaObject().toDebugString();
};
/**
* @returns {module:eclairjs/ml/util.MLWriter}
*/
GBTClassificationModel.prototype.write = function() {
var javaObject = this.getJavaObject().write();
return Utils.javaToJs(javaObject);
};
//
// static methods
//
/**
* @returns {module:eclairjs/ml/util.MLReader}
*/
GBTClassificationModel.read = function() {
var javaObject = org.apache.spark.ml.classification.GBTClassificationModel.read();
return Utils.javaToJs(javaObject);
};
/**
* @param {string} path
* @returns {module:eclairjs/ml/classification.GBTClassificationModel}
*/
GBTClassificationModel.load = function(path) {
var javaObject = org.apache.spark.ml.classification.GBTClassificationModel.load(path);
return new GBTClassificationModel(javaObject);
};
module.exports = GBTClassificationModel;
})();