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c1b1a5d6ac
* Multiple training data sets allowed * Tests with multiple training data sets * Updating docs according to #38 Documenting all models which predictions will be based on all training data provided. Some models already supported multiple training data sets.
726 B
726 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 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']