/*
* Copyright 2015 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 JavaWrapper = require(EclairJS_Globals.NAMESPACE + '/JavaWrapper');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
/**
* @constructor
* @memberof module:eclairjs/mllib/regression
* @classdesc GeneralizedLinearModel (GLM) represents a model trained using GeneralizedLinearAlgorithm.
* GLMs consist of a weight vector and an intercept.
* @param {module:eclairjs/mllib/linalg.Vector} weights
* @param {float} intercept
*/
var GeneralizedLinearModel = function(jvmObj) {
this.logger = Logger.getLogger("mllib.regression.GeneralizedLinearModel_js");
JavaWrapper.call(this, jvmObj);
};
GeneralizedLinearModel.prototype = Object.create(JavaWrapper.prototype);
GeneralizedLinearModel.prototype.constructor = GeneralizedLinearModel;
/**
* Predict values for a single data point using the model trained.
* @param {module:eclairjs/mllib/linalg.Vector} testData
* @returns {float}
*/
GeneralizedLinearModel.prototype.predict = function(testData) {
return this.getJavaObject().predict(Utils.unwrapObject(testData));
};
module.exports = GeneralizedLinearModel;
})();