/*
* 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 RegressionModel = require('./RegressionModel')();
var gKernelP = kernelP;
/**
* @classdesc
* :: Experimental ::
* Model produced by {@link module:eclairjs/ml/regression.GeneralizedLinearRegression}.
* @class
* @extends module:eclairjs/mllib/regression.RegressionModel
* @memberof module:eclairjs/ml/regression
*/
function GeneralizedLinearRegressionModel() {
Utils.handleConstructor(this, arguments, gKernelP);
}
GeneralizedLinearRegressionModel.prototype = Object.create(RegressionModel.prototype);
GeneralizedLinearRegressionModel.prototype.constructor = GeneralizedLinearRegressionModel;
/**
* An immutable unique ID for the object and its derivatives.
* @returns {Promise.<string>}
*/
GeneralizedLinearRegressionModel.prototype.uid = function () {
var args = {
target: this,
method: 'uid',
args: Utils.wrapArguments(arguments),
returnType: String
};
return Utils.generate(args);
};
/**
* Sets the link prediction (linear predictor) column name.
*
* @param {string} value
* @returns * @returns {module:eclairjs/ml/regression.GeneralizedLinearRegressionModel}
*/
GeneralizedLinearRegressionModel.prototype.setLinkPredictionCol = function(value) {
var args ={
target: this,
method: 'setLinkPredictionCol',
args: Utils.wrapArguments(arguments),
returnType: GeneralizedLinearRegressionModel
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/sql.Dataset} dataset
* @returns {module:eclairjs/sql.Dataset}
*/
GeneralizedLinearRegressionModel.prototype.transform = function(dataset) {
var Dataset = require('../../sql/Dataset');
var args ={
target: this,
method: 'transform',
args: Utils.wrapArguments(arguments),
returnType: Dataset
};
return Utils.generate(args);
};
/**
* 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}
*/
GeneralizedLinearRegressionModel.prototype.summary = function() {
var GeneralizedLinearRegressionTrainingSummary = require('./GeneralizedLinearRegressionTrainingSummary')();
var args = {
target: this,
method: 'summary',
args: Utils.wrapArguments(arguments),
returnType: GeneralizedLinearRegressionTrainingSummary
};
return Utils.generate(args);
};
/**
* Indicates if {@link module:eclairjs/ml/regression.GeneralizedLinearRegressionTrainingSummary} is available.
* @returns {Promise.<boolean>}
*/
GeneralizedLinearRegressionModel.prototype.hasSummary = function() {
var args = {
target: this,
method: 'hasSummary',
args: Utils.wrapArguments(arguments),
returnType: Boolean
};
return Utils.generate(args);
};
/**
* 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}
*/
GeneralizedLinearRegressionModel.prototype.evaluate = function(dataset) {
var GeneralizedLinearRegressionSummary = require('./GeneralizedLinearRegressionSummary')();
var args ={
target: this,
method: 'evaluate',
args: Utils.wrapArguments(arguments),
returnType: GeneralizedLinearRegressionSummary
};
return Utils.generate(args);
};
/**
* @returns {module:eclairjs/ml/linalg.Vector}
*/
GeneralizedLinearRegressionModel.prototype.coefficients = function () {
var Vector = require('../linalg/Vector')();
var args = {
target: this,
method: 'coefficients',
args: Utils.wrapArguments(arguments),
returnType: Vector
};
return Utils.generate(args);
};
/**
*
* @returns {Promise.<number>}
*/
GeneralizedLinearRegressionModel.prototype.intercept = function () {
var args = {
target: this,
method: 'intercept',
args: Utils.wrapArguments(arguments),
returnType: Number
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/mllib/regression.GeneralizedLinearRegressionModel}
*/
GeneralizedLinearRegressionModel.prototype.copy = function(extra) {
var args = {
target: this,
method: 'copy',
args: Utils.wrapArguments(arguments),
returnType: GeneralizedLinearRegressionModel
};
return Utils.generate(args);
};
/**
* Returns a {@link MLWriter} instance for this ML instance.
*
* For [[GeneralizedLinearRegressionModel]], this does NOT currently save the training {@link summary}.
* An option to save {@link summary} may be added in the future.
*
* This also does not save the {@link parent} currently.
* @returns {MLWriter}
*/
GeneralizedLinearRegressionModel.prototype.write = function() {
throw "not implemented by ElairJS";
// var args ={
// target: this,
// method: 'write',
// returnType: MLWriter
//
// };
//
// return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {MLReader}
*/
GeneralizedLinearRegressionModel.read = function() {
throw "not implemented by ElairJS";
// var args ={
// target: GeneralizedLinearRegressionModel,
// method: 'read',
// returnType: MLReader
//
// };
//
// return Utils.generate(args);
};
/**
* @param {string} path
* @returns {module:eclairjs/mllib/regression.GeneralizedLinearRegressionModel}
*/
GeneralizedLinearRegressionModel.load = function(path) {
var args = {
target: GeneralizedLinearRegressionModel,
method: 'load',
args: Utils.wrapArguments(arguments),
static: true,
kernelP: gKernelP,
returnType: GeneralizedLinearRegressionModel
};
return Utils.generate(args);
};
GeneralizedLinearRegressionModel.moduleLocation = '/ml/regression/GeneralizedLinearRegressionModel';
return GeneralizedLinearRegressionModel;
})();
};