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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | 42x 42x 29x 29x 10x 10x 1x 9x 9x 9x 47x 9x 8x 8x 1x 5x 42x 42x | /* * 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 BinaryNeuralNetworkClassifier = require('../classifiers/binary-neural-network-classifier'); /** * Class for the Logistic Regression NLU */ class BinaryNeuralNetworkNLU extends BaseNLU { /** * Constructor of the class. * @param {Object} settings Settings for this instance. */ constructor(settings) { super(settings); this.classifier = this.settings.classifier || new BinaryNeuralNetworkClassifier(); } /** * Train the classifier */ async train() { 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 (input.length > 0) { await this.classifier.trainBatch(input); 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) { return this.normalizeNeural( this.classifier.getClassifications(this.textToFeatures(utterance)) ); } } BaseNLU.classes.BinaryNeuralNetworkNLU = BinaryNeuralNetworkNLU; module.exports = BinaryNeuralNetworkNLU; |