simple Naive Bayes classifier

src/Phpml/Classifier/NaiveBayes.php

@@ -6,12 +6,24 @@ namespace Phpml\Classifier;
 
 class NaiveBayes implements Classifier
 {
+    /**
+     * @var array
+     */
+    private $samples;
+
+    /**
+     * @var array
+     */
+    private $labels;
+
     /**
      * @param array $samples
      * @param array $labels
      */
     public function train(array $samples, array $labels)
     {
+        $this->samples = $samples;
+        $this->labels = $labels;
     }
 
     /**
@@ -21,5 +33,38 @@ class NaiveBayes implements Classifier
      */
     public function predict(array $samples)
     {
+        if (!is_array($samples[0])) {
+            $predicted = $this->predictSample($samples);
+        } else {
+            $predicted = [];
+            foreach ($samples as $index => $sample) {
+                $predicted[$index] = $this->predictSample($sample);
+            }
+        }
+
+        return $predicted;
+    }
+
+    /**
+     * @param array $sample
+     *
+     * @return mixed
+     */
+    private function predictSample(array $sample)
+    {
+        $predictions = [];
+        foreach ($this->labels as $index => $label) {
+            $predictions[$label] = 0;
+            foreach ($sample as $token => $count) {
+                if (array_key_exists($token, $this->samples[$index])) {
+                    $predictions[$label] += $count * $this->samples[$index][$token];
+                }
+            }
+        }
+
+        arsort($predictions, SORT_NUMERIC);
+        reset($predictions);
+
+        return key($predictions);
     }
 }

tests/Phpml/Classifier/NaiveBayesTest.php

@@ -0,0 +1,38 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace tests\Classifier;
+
+use Phpml\Classifier\NaiveBayes;
+
+class NaiveBayesTest extends \PHPUnit_Framework_TestCase
+{
+    public function testPredictSingleSample()
+    {
+        $samples = [[5, 1, 1], [1, 5, 1], [1, 1, 5]];
+        $labels = ['a', 'b', 'c'];
+
+        $classifier = new NaiveBayes();
+        $classifier->train($samples, $labels);
+
+        $this->assertEquals('a', $classifier->predict([3, 1, 1]));
+        $this->assertEquals('b', $classifier->predict([1, 4, 1]));
+        $this->assertEquals('c', $classifier->predict([1, 1, 6]));
+    }
+
+    public function testPredictArrayOfSamples()
+    {
+        $trainSamples = [[5, 1, 1], [1, 5, 1], [1, 1, 5]];
+        $trainLabels = ['a', 'b', 'c'];
+
+        $testSamples = [[3, 1, 1], [5, 1, 1], [4, 3, 8], [1, 1, 2], [2, 3, 2], [1, 2, 1], [9, 5, 1], [3, 1, 2]];
+        $testLabels = ['a', 'a', 'c', 'c', 'b', 'b', 'a', 'a'];
+
+        $classifier = new NaiveBayes();
+        $classifier->train($trainSamples, $trainLabels);
+        $predicted = $classifier->predict($testSamples);
+
+        $this->assertEquals($testLabels, $predicted);
+    }
+}