/*
* Copyright (c) AXA Shared Services Spain S.A.
*
* Permission is hereby granted, free of charge, to any person obtaining
* a copy of this software and associated documentation files (the
* "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish,
* distribute, sublicense, and/or sell copies of the Software, and to
* permit persons to whom the Software is furnished to do so, subject to
* the following conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
* LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
* OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
* WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
const Classifier = require('./classifier');
const { Mathops } = require('../math');
/**
* Class for a Bayes Classifier.
*/
class BayesClassifier extends Classifier {
setSmoothing(newSmoothing) {
this.smoothing = newSmoothing;
}
/**
* Calculate the probability of a class (label) given an observation.
*
* @param {Vector} observation Observation vector.
* @param {String} label Label of the class.
* @returns {Number} Value of probability of class.
* @memberof BayesClassifier
*/
getProbabilityOfClass(observation, label) {
const smoothing = this.smoothing || 1.0;
let probability = 0;
const classTotal = this.observations[label].length;
observation.forEach((feature, index) => {
if (feature) {
let count = 0;
this.observations[label].forEach(classObservation => {
count += classObservation[index];
});
const value = count || smoothing;
probability += Math.log(value / classTotal);
}
});
probability = (classTotal / this.observationCount) * Math.exp(probability);
return probability;
}
/**
* Given an observation and an array for inserting the results,
* it calculates the score of the observation for each of the classifications
* and fills the array with the result objects.
* @param {Object} srcObservation Source observation.
* @param {Object[]} classifications Array of classifications.
* @memberof BayesClassifier
*/
classifyObservation(srcObservation, classifications) {
const observation = Mathops.asVector(srcObservation);
Object.keys(this.observations).forEach(label => {
const value = this.getProbabilityOfClass(observation, label);
classifications.push({
label,
value,
});
});
}
}
module.exports = BayesClassifier;
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