/*
* 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 ProbabilisticClassificationModel = require('./ProbabilisticClassificationModel')();
var gKernelP = kernelP;
/**
* @classdesc
* Model produced by {@link module:eclairjs/ml/classification.LogisticRegression}.
* @class
* @memberof module:eclairjs/ml/classification
* @extends module:eclairjs/ml/classification.ProbabilisticClassificationModel
*/
function LogisticRegressionModel() {
Utils.handleConstructor(this, arguments, gKernelP);
}
LogisticRegressionModel.prototype = Object.create(ProbabilisticClassificationModel.prototype);
LogisticRegressionModel.prototype.constructor = LogisticRegressionModel;
/**
* @returns {module:eclairjs/mllib/linalg.Vector}
*/
LogisticRegressionModel.prototype.coefficients = function () {
var Vector = require('../../mllib/linalg/Vector');
var args = {
target: this,
method: 'coefficients',
args: Utils.wrapArguments(arguments),
returnType: Vector
};
return Utils.generate(args);
};
/**
*
* @returns {Promise.<number>}
*/
LogisticRegressionModel.prototype.intercept = function () {
var args = {
target: this,
method: 'intercept',
args: Utils.wrapArguments(arguments),
returnType: Number
};
return Utils.generate(args);
};
/**
* @param {number} value
* @returns {module:eclairjs/mllib/classification.LogisticRegressionModel}
*/
LogisticRegressionModel.prototype.setThreshold = function(value) {
var args = {
target: this,
method: 'setThreshold',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionModel
};
return Utils.generate(args);
};
/**
* @returns {Promise.<number>}
*/
LogisticRegressionModel.prototype.getThreshold = function() {
var args = {
target: this,
method: 'getThreshold',
args: Utils.wrapArguments(arguments),
returnType: Number
};
return Utils.generate(args);
};
/**
* @param {number[]} value
* @returns {module:eclairjs/mllib/classification.LogisticRegressionModel}
*/
LogisticRegressionModel.prototype.setThresholds = function(value) {
var args = {
target: this,
method: 'setThresholds',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionModel
};
return Utils.generate(args);
};
/**
* @returns {Promise.<number[]>}
*/
LogisticRegressionModel.prototype.getThresholds = function() {
var args = {
target: this,
method: 'getThresholds',
args: Utils.wrapArguments(arguments),
returnType: [Number]
};
return Utils.generate(args);
};
/**
* Gets summary of model on training set. An exception is
* thrown if `trainingSummary == None`.
* @returns {module:eclairjs/ml/classification.LogisticRegressionTrainingSummary}
*/
LogisticRegressionModel.prototype.summary = function() {
var LogisticRegressionTrainingSummary = require('./LogisticRegressionTrainingSummary')();
var args = {
target: this,
method: 'summary',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionTrainingSummary
};
return Utils.generate(args);
};
/**
* Indicates whether a training summary exists for this model instance.
* @returns {Promise.<boolean>}
*/
LogisticRegressionModel.prototype.hasSummary = function() {
var args = {
target: this,
method: 'hasSummary',
args: Utils.wrapArguments(arguments),
returnType: Boolean
};
return Utils.generate(args);
};
/**
* Evaluates the model on a test dataset.
* @param {module:eclairjs/sql.Dataset} dataset Test dataset to evaluate model on.
* @returns {LogisticRegressionSummary}
*/
LogisticRegressionModel.prototype.evaluate = function(dataset) {
var LogisticRegressionSummary = require('../../ml/classification/LogisticRegressionSummary.js');
var args ={
target: this,
method: 'evaluate',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionSummary
};
return Utils.generate(args);
};
/**
* @param {module:eclairjs/ml/param.ParamMap} extra
* @returns {module:eclairjs/mllib/classification.LogisticRegressionModel}
*/
LogisticRegressionModel.prototype.copy = function(extra) {
var args = {
target: this,
method: 'hasSummary',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionModel
};
return Utils.generate(args);
};
/**
* Returns a {@link MLWriter} instance for this ML instance.
*
* For [[LogisticRegressionModel]], 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}
*/
LogisticRegressionModel.prototype.write = function() {
throw "not implemented by ElairJS";
// var args ={
// target: this,
// method: 'write',
// returnType: MLWriter
//
// };
//
// return Utils.generate(args);
};
/**
*
* @returns {module:eclairjs/mllib/classification.LogisticRegression}
*/
LogisticRegressionModel.prototype.parent = function() {
var LogisticRegression = require('./LogisticRegression')();
var args = {
target: this,
method: 'parent',
args: Utils.wrapArguments(arguments),
returnType: LogisticRegression
};
return Utils.generate(args);
};
//
// static methods
//
/**
* @returns {MLReader}
*/
LogisticRegressionModel.read = function() {
throw "not implemented by ElairJS";
// var args ={
// target: LogisticRegressionModel,
// method: 'read',
// returnType: MLReader
//
// };
//
// return Utils.generate(args);
};
/**
* @param {string} path
* @returns {module:eclairjs/mllib/classification.LogisticRegressionModel}
*/
LogisticRegressionModel.load = function(path) {
var args = {
target: LogisticRegressionModel,
method: 'load',
kernelP: gKernelP,
static: true,
args: Utils.wrapArguments(arguments),
returnType: LogisticRegressionModel
};
return Utils.generate(args)
};
LogisticRegressionModel.moduleLocation = '/ml/classification/LogisticRegressionModel';
return LogisticRegressionModel;
})();
};