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