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732 B
732 B
NaiveBayes Classifier
Classifier based on applying Bayes' theorem with strong (naive) independence assumptions between the features.
Train
To train a classifier, simply provide train samples and labels (as array
). Example:
$samples = [[5, 1, 1], [1, 5, 1], [1, 1, 5]];
$labels = ['a', 'b', 'c'];
$classifier = new NaiveBayes();
$classifier->train($samples, $labels);
You can train the classifier using multiple data sets, predictions will be based on all the training data.
Predict
To predict sample label use the predict
method. You can provide one sample or array of samples:
$classifier->predict([3, 1, 1]);
// return 'a'
$classifier->predict([[3, 1, 1], [1, 4, 1]]);
// return ['a', 'b']