119 lines
5.1 KiB
JavaScript
119 lines
5.1 KiB
JavaScript
/*
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Copyright (c) 2011, Chris Umbel
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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var LogisticRegressionClassifier = new require('../lib/apparatus/classifier/logistic_regression_classifier');
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describe('logistic regression', function() {
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it('should classify with examples added in groups', function() {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1,1,1,0,0,0], 'one');
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logistic.addExample([1,0,1,0,0,0], 'one');
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logistic.addExample([1,1,1,0,0,0], 'one');
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logistic.addExample([0,0,0,1,1,1], 'two');
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logistic.addExample([0,0,0,1,0,1], 'two');
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logistic.addExample([0,0,0,1,1,0], 'two');
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logistic.train();
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expect(logistic.classify([0,1,1,0,0,0])).toBe('one');
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expect(logistic.classify([0,0,0,0,1,1])).toBe('two');
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});
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it('should classify', function() {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,0,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([0,0,0,1,1,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,0,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,1,0,0,0,0], 'two');
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logistic.addExample([0,0,0,0,0,0,1,1,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,0,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,1,0], 'three');
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logistic.train();
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expect(logistic.classify([1,1,0,0,0,0,1,0,0])).toBe('one');
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expect(logistic.classify([0,0,1,1,1,0,0,0,1])).toBe('two');
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expect(logistic.classify([1,0,0,0,1,0,0,1,1])).toBe('three');
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});
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it('should allow retraining', function() {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,0,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([0,0,0,1,1,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,0,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,1,0,0,0,0], 'two');
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logistic.train();
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logistic.addExample([0,0,0,0,0,0,1,1,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,0,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,1,0], 'three');
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logistic.train();
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expect(logistic.classify([1,1,0,0,0,0,1,0,0])).toBe('one');
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expect(logistic.classify([0,0,1,1,1,0,0,0,1])).toBe('two');
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expect(logistic.classify([1,0,0,0,1,0,0,1,1])).toBe('three');
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});
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it('should classify', function() {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,0,1,0,0,0,0,0,0], 'one');
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logistic.addExample([1,1,1,0,0,0,0,0,0], 'one');
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logistic.addExample([0,0,0,1,1,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,0,1,0,0,0], 'two');
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logistic.addExample([0,0,0,1,1,0,0,0,0], 'two');
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logistic.addExample([0,0,0,0,0,0,1,1,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,0,1], 'three');
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logistic.addExample([0,0,0,0,0,0,1,1,0], 'three');
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logistic.train();
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var obj = JSON.stringify(logistic);
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var newLogistic = LogisticRegressionClassifier.restore(JSON.parse(obj));
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expect(newLogistic.classify([1,1,0,0,0,0,1,0,0])).toBe('one');
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expect(newLogistic.classify([0,0,1,1,1,0,0,0,1])).toBe('two');
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expect(newLogistic.classify([1,0,0,0,1,0,0,1,1])).toBe('three');
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});
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it('should not run into an infinite loop (1)', function () {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1, 1, 1, 0, 0, 0, 0, 0, 0], 'one');
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logistic.addExample([1, 1, 1, 0, 0, 0, 0, 0, 0], 'two');
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logistic.train();
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});
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it('should not run into an infinite loop (2)', function () {
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var logistic = new LogisticRegressionClassifier();
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logistic.addExample([1, 1, 1, 0, 0, 0, 0, 0, 0], 'one');
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logistic.addExample([1, 1, 1, 0, 0, 0, 0, 0, 0], 'two');
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logistic.addExample([1, 1, 1, 0, 0, 0, 0, 0, 0], 'three');
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logistic.train();
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});
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});
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