php-ml/docs/machine-learning/classification/naive-bayes.md

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# 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:
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```
$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.
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### Predict
To predict sample label use the `predict` method. You can provide one sample or array of samples:
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```
$classifier->predict([3, 1, 1]);
// return 'a'
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$classifier->predict([[3, 1, 1], [1, 4, 1]]);
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// return ['a', 'b']
```