/*
* 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 RegressionModel = require(EclairJS_Globals.NAMESPACE + '/ml/regression/RegressionModel');
var Logger = require(EclairJS_Globals.NAMESPACE + '/Logger');
var Utils = require(EclairJS_Globals.NAMESPACE + '/Utils');
//var GeneralizedLinearRegressionModel = Java.type('org.apache.spark.ml.regression.GeneralizedLinearRegressionModel');
/**
* @classdesc
* :: Experimental ::
* Model produced by {@link GeneralizedLinearRegression}.
* @class
* @memberof module:eclairjs/ml/regression
* @extends module:eclairjs/ml/regression.RegressionModel
*/
var GeneralizedLinearRegressionModel = function(jvmObject) {
this.logger = Logger.getLogger("ml_regression_GeneralizedLinearRegressionModel_js");
RegressionModel.call(this, jvmObject);
};
GeneralizedLinearRegressionModel.prototype = Object.create(RegressionModel.prototype);
GeneralizedLinearRegressionModel.prototype.constructor = GeneralizedLinearRegressionModel;
/**
* @returns {module:eclairjs/ml/linalg.Vector}
*/
GeneralizedLinearRegressionModel.prototype.coefficients = function () {
var javaObject = this.getJavaObject().coefficients();
return Utils.javaToJs(javaObject);
};
/**
*
* @returns {double}
*/
GeneralizedLinearRegressionModel.prototype.intercept = function () {
return Utils.javaToJs(this.getJavaObject().intercept());
};
/**
* Sets the link prediction (linear predictor) column name.
*
* @param {string} value
* @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionModel}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#setLinkPredictionCol
*/
GeneralizedLinearRegressionModel.prototype.setLinkPredictionCol = function(value) {
var javaObject = this.getJavaObject().setLinkPredictionCol(value);
return new GeneralizedLinearRegressionModel(javaObject);
};
/**
* @param {module:eclairjs/sql.Dataset} dataset
* @returns {DataFrame}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#transform
*/
GeneralizedLinearRegressionModel.prototype.transform = function(dataset) {
var dataset_uw = Utils.unwrapObject(dataset);
var javaObject = this.getJavaObject().transform(dataset_uw);
return Utils.javaToJs(javaObject);
};
/**
* Gets R-like summary of model on training set. An exception is
* thrown if there is no summary available.
* @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionTrainingSummary}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#summary
*/
GeneralizedLinearRegressionModel.prototype.summary = function() {
var javaObject = this.getJavaObject().summary();
return Utils.javaToJs(javaObject);
};
/**
* Indicates if {@link summary} is available.
* @returns {boolean}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#hasSummary
*/
GeneralizedLinearRegressionModel.prototype.hasSummary = function() {
return this.getJavaObject().hasSummary();
};
/**
* Evaluate the model on the given dataset, returning a summary of the results.
* @param {module:eclairjs/sql.Dataset} dataset
* @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionSummary}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#evaluate
*/
GeneralizedLinearRegressionModel.prototype.evaluate = function(dataset) {
var dataset_uw = Utils.unwrapObject(dataset);
var javaObject = this.getJavaObject().evaluate(dataset_uw);
return Utils.javaToJs(javaObject);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionModel}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#copy
*/
GeneralizedLinearRegressionModel.prototype.copy = function(extra) {
var extra_uw = Utils.unwrapObject(extra);
var javaObject = this.getJavaObject().copy(extra_uw);
return new GeneralizedLinearRegressionModel(javaObject);
};
/**
* Returns a {@link MLWriter} instance for this ML instance.
*
* For {@link GeneralizedLinearRegressionModel}, this does NOT currently save the
* training [[summary]]. An option to save {@link summary} may be added in the future.
*
* @returns {module:eclairjs/ml/util.MLWriter}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#write
*/
GeneralizedLinearRegressionModel.prototype.write = function() {
var javaObject = this.getJavaObject().write();
return Utils.javaToJs(javaObject);
};
//
// static methods
//
/**
* @returns {module:eclairjs/ml/util.MLReader}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#read
* @static
*/
GeneralizedLinearRegressionModel.read = function() {
var javaObject = org.apache.spark.ml.regression.GeneralizedLinearRegressionModel.read();
return Utils.javaToJs(javaObject);
};
/**
* @param {string} path
* @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionModel}
* @function
* @name module:eclairjs/ml/regression.GeneralizedLinearRegressionModel#load
* @static
*/
GeneralizedLinearRegressionModel.load = function(path) {
var javaObject = org.apache.spark.ml.regression.GeneralizedLinearRegressionModel.load(path);
return new GeneralizedLinearRegressionModel(javaObject);
};
module.exports = GeneralizedLinearRegressionModel;
})();