Apply cs fixes for NaiveBayes

src/Phpml/Classification/NaiveBayes.php

@@ -12,24 +12,62 @@ use Phpml\Math\Statistic\StandardDeviation;
 class NaiveBayes implements Classifier
 {
     use Trainable, Predictable;
+
     const CONTINUOS    = 1;
     const NOMINAL    = 2;
     const EPSILON = 1e-10;
-    private $std = array();
+
-    private $mean= array();
+    /**
-    private $discreteProb = array();
+     * @var array
-    private $dataType = array();
+     */
-    private $p = array();
+    private $std = [];
+
+    /**
+     * @var array
+     */
+    private $mean= [];
+
+    /**
+     * @var array
+     */
+    private $discreteProb = [];
+
+    /**
+     * @var array
+     */
+    private $dataType = [];
+
+    /**
+     * @var array
+     */
+    private $p = [];
+
+    /**
+     * @var int
+     */
     private $sampleCount = 0;
+
+    /**
+     * @var int
+     */
     private $featureCount = 0;
-    private $labels = array();
+
+    /**
+     * @var array
+     */
+    private $labels = [];
+
+    /**
+     * @param array $samples
+     * @param array $targets
+     */
     public function train(array $samples, array $targets)
     {
         $this->samples = $samples;
         $this->targets = $targets;
         $this->sampleCount = count($samples);
         $this->featureCount = count($samples[0]);
-        // Get distinct targets
+
         $this->labels = $targets;
         array_unique($this->labels);
         foreach ($this->labels as $label) {
@@ -79,6 +117,7 @@ class NaiveBayes implements Classifier
      * @param array $sample
      * @param int $feature
      * @param string $label
+     * @return float
      */
     private function sampleProbability($sample, $feature, $label)
     {