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* Copyright (c) AXA Group Operations 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 BaseNLU = require('./base-nlu');
const BrainClassifier = require('../classifiers/brain-classifier');
const NlpUtil = require('../nlp/nlp-util');
/**
* Class for the Logistic Regression NLU
*/
class BrainNLU extends BaseNLU {
/**
* Constructor of the class.
* @param {Object} settings Settings for this instance.
*/
constructor(settings) {
super(settings);
if (this.settings.useNoneFeature === undefined) {
this.settings.useNoneFeature =
NlpUtil.useNoneFeature[this.settings.language] || false;
}
this.classifier = this.settings.classifier || new BrainClassifier(settings);
}
/**
* Train the classifier
*/
async train(createNetwork = true) {
const mustTrain = this.isEditing ? this.endEdit() : true;
if (!mustTrain) {
return false;
}
this.classifier.clear();
const input = [];
this.docs.forEach(doc => {
input.push({
input: this.textToFeatures(doc.tokens),
output: doc.intent,
});
});
if (this.settings.useNoneFeature) {
input.push({
input: this.textToFeatures('nonefeature'),
output: 'None',
});
}
if (input.length > 0) {
await this.classifier.trainBatch(input, createNetwork);
return true;
}
return false;
}
/**
* Get all the labels and score for each label from this utterance.
* @param {String} utterance Utterance to be classified.
* @returns {Object[]} Sorted array of classifications, with label and score.
*/
getClassifications(utterance) {
const tokens = this.textToFeatures(utterance);
const whitelist = this.getWhitelist(tokens);
Eif (!whitelist.includes('None')) {
whitelist.push('None');
}
const classifications = this.classifier.getClassifications(tokens);
for (let i = 0; i < classifications.length; i += 1) {
const classification = classifications[i];
if (!whitelist.includes(classification.label)) {
classification.value = 0;
}
}
return this.normalizeNeural(classifications);
}
}
BaseNLU.classes.BrainNLU = BrainNLU;
module.exports = BrainNLU;
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