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umd.js
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umd.js
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const neuro = require('../dist/index.umd.js');
// First, define our base classifier type (a multi-label classifier based on winnow):
var TextClassifier = neuro.classifiers.multilabel.BinaryRelevance.bind(0, {
binaryClassifierType: neuro.classifiers.Winnow.bind(0, { retrain_count: 10 })
});
// Now define our feature extractor - a function that takes a sample and adds features to a given features set:
var WordExtractor = function(input, features) {
input.split(" ").forEach(function(word) {
features[word] = 1;
});
};
// Initialize a classifier with the base classifier type and the feature extractor:
var intentClassifier = new neuro.classifiers.EnhancedClassifier({
classifierType: TextClassifier,
featureExtractor: WordExtractor
});
// Train and test:
intentClassifier.trainBatch([
{ input: "안녕하세요.", output: "안녕하세요." },
{ input: "반가워요", output: "방가" },
]);
console.dir(intentClassifier.classify("안녕"));
console.dir(intentClassifier.classify("안녕하세요."));
console.dir(intentClassifier.classify("방가방가"));
console.dir(intentClassifier.classify("방가"));
console.dir(intentClassifier.classify("반가워요"));