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<h1 class="page-title">Source: classifiers/classifier.js</h1>
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<pre class="prettyprint source linenums"><code>/*
* 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.
*/
/**
* Class for a generic classifier.
* This is an abstract class that must be implemented by subclasses that
* contains the real classifier algorithm.
*/
class Classifier {
/**
* Constructor of the class.
* Initialize the basic properties and structure of any classifier.
* @param {Object} settings Settings for initializing the instance.
*/
constructor(settings) {
this.settings = settings || {};
this.clear();
}
/**
* Clears the content of the instance.
* This is done by initializing the observations object, the labels array
* and the observation count.
*/
clear() {
this.observations = {};
this.labels = [];
this.observationCount = 0;
}
/**
* Adds a new label to the observation tree. If the label already exists,
* return the existing one without creating it again.
* @param {String} label Label to be created or getted.
* @returns {String[]} List of observations assigned to this label.
*/
addLabel(label) {
if (!this.observations[label]) {
this.observations[label] = [];
this.labels.push(label);
}
return this.observations[label];
}
/**
* Adds a new observation to the classifier.
* @param {String} observation Observation to be added.
* @param {String} label Label of the observation.
*/
addObservation(observation, label) {
const labelObservations = this.addLabel(label);
labelObservations.push(observation);
this.observationCount += 1;
}
/**
* Removes an observation from the observation list of a label.
* @param {String} observation Observation to be removed.
* @param {String} label Label where we want the observation to be removed.
*/
removeObservationByLabel(observation, label) {
if (this.observations[label]) {
const labelObservations = this.observations[label];
const index = labelObservations.indexOf(observation);
if (index !== -1) {
labelObservations.splice(index, 1);
if (labelObservations.length === 0) {
delete this.observations[label];
this.labels.splice(this.labels.indexOf(label), 1);
}
this.observationCount -= 1;
}
}
}
/**
* Removes an observation. The label of the observation can be passed or
* can be omitted. When omitted, it loops over all labels tryin to remove
* the given observation.
* @param {String} observation Observation to be removed.
* @param {String} label Label of the observation, or undefined to iterate over
* all labels.
*/
removeObservation(observation, label) {
if (label) {
this.removeObservationByLabel(observation, label);
} else {
for (let i = 0; i < this.labels.length; i += 1) {
this.removeObservationByLabel(observation, this.labels[i]);
}
}
}
/**
* Iterate all the observations to calculate the total observation count.
*/
recalculateObservationCount() {
let count = 0;
for (let i = 0, l = this.labels.length; i < l; i += 1) {
if (this.observations[this.labels[i]]) {
count += this.observations[this.labels[i]].length;
}
}
this.observationCount = count;
}
/**
* Classify one observation.
*/
classifyObservation() {
throw new Error(
'This method is not implemented. Must be implemented by child classes.'
);
}
/**
* Get all the labels and score for each label from one observation.
* @param {String} observation Observation to be classified.
* @returns {Object[]} Sorted array of classifications, that means label and the score.
*/
getClassifications(observation) {
const labels = [];
this.classifyObservation(observation, labels);
return labels.sort((x, y) => y.value - x.value);
}
/**
* Given an observation, get the label and score of the best classification.
* @param {String} observation Observation to be classified.
* @returns {Object} Best classification of the observation.
*/
getBestClassification(observation) {
const classifications = this.getClassifications(observation);
if (!classifications || classifications.length === 0) {
return undefined;
}
return classifications[0];
}
/**
* Creates a matrix filled with zeros, that relate every single observation
* with every single label.
* @returns {Number[][]} A bidimensional array where x is the observation
* and y is the label, filled to zeros.
*/
createClassificationMatrix() {
const result = [];
for (let i = 0; i < this.observationCount; i += 1) {
const classification = [];
result.push(classification);
for (let j = 0, l = this.labels.length; j < l; j += 1) {
classification.push(0);
}
}
return result;
}
}
module.exports = Classifier;
</code></pre>
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<h2><a href="index.html">Home</a></h2><h3>Classes</h3><ul><li><a href="BinaryNeuralNetworkClassifier.html">BinaryNeuralNetworkClassifier</a></li><li><a href="Classifier.html">Classifier</a></li><li><a href="ConversationContext.html">ConversationContext</a></li><li><a href="DutchStemmer.html">DutchStemmer</a></li><li><a href="EnglishStemmer.html">EnglishStemmer</a></li><li><a href="EnumNamedEntity.html">EnumNamedEntity</a></li><li><a href="Evaluator.html">Evaluator</a></li><li><a href="HungarianStemmer.html">HungarianStemmer</a></li><li><a href="ItalianStemmer.html">ItalianStemmer</a></li><li><a href="Language.html">Language</a></li><li><a href="LogisticRegressionClassifier.html">LogisticRegressionClassifier</a></li><li><a href="Matrix.html">Matrix</a></li><li><a href="MemoryConversationContext.html">MemoryConversationContext</a></li><li><a href="NamedEntity.html">NamedEntity</a></li><li><a href="NerManager.html">NerManager</a></li><li><a href="NlgManager.html">NlgManager</a></li><li><a href="NlpClassifier.html">NlpClassifier</a></li><li><a href="NlpManager.html">NlpManager</a></li><li><a href="NorwegianStemmer.html">NorwegianStemmer</a></li><li><a href="PortugueseStemmer.html">PortugueseStemmer</a></li><li><a href="Recognizer.html">Recognizer</a></li><li><a href="RegexNamedEntity.html">RegexNamedEntity</a></li><li><a href="RomanianStemmer.html">RomanianStemmer</a></li><li><a href="RussianStemmer.html">RussianStemmer</a></li><li><a href="SentimentAnalyzer.html">SentimentAnalyzer</a></li><li><a href="SentimentManager.html">SentimentManager</a></li><li><a href="SimilarSearch.html">SimilarSearch</a></li><li><a href="SlotManager.html">SlotManager</a></li><li><a href="StemmerJa.html">StemmerJa</a></li><li><a href="SwedishStemmer.html">SwedishStemmer</a></li><li><a href="Tokenizer.html">Tokenizer</a></li><li><a href="TrimNamedEntity.html">TrimNamedEntity</a></li><li><a href="TurkishStemmer.html">TurkishStemmer</a></li><li><a href="Vector.html">Vector</a></li><li><a href="XTable.html">XTable</a></li></ul><h3>Global</h3><ul><li><a href="global.html#endsinArr">endsinArr</a></li><li><a href="global.html#prelude">prelude</a></li><li><a href="global.html#regions">regions</a></li><li><a href="global.html#stem">stem</a></li><li><a href="global.html#stopwords">stopwords</a></li></ul>
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