php-ai / php-ml

src/Phpml/Classification/Ensemble/Bagging.php

Doc Comments +1 added lines

@@ -114,6 +114,7 @@
     }
 
     /**
+     * @param integer $index
      * @return array
      */
     protected function getRandomSubset($index)

Unused Use Statements -2 removed lines

@@ -6,10 +6,8 @@
 
 use Phpml\Helper\Predictable;
 use Phpml\Helper\Trainable;
-use Phpml\Math\Statistic\Mean;
 use Phpml\Classification\Classifier;
 use Phpml\Classification\DecisionTree;
-use Phpml\Classification\NaiveBayes;
 
 class Bagging implements Classifier
 {

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 
@@ -118,13 +118,13 @@ 
      */
     protected function getRandomSubset($index)
     {
-        $subsetLength = (int)ceil(sqrt($this->numSamples));
+        $subsetLength = (int) ceil(sqrt($this->numSamples));
         $denom = $this->subsetRatio / 2;
         $subsetLength = $this->numSamples / (1 / $denom);
         $index = $index * $subsetLength % $this->numSamples;
         $samples = [];
         $targets = [];
-        for ($i=0; $i<$subsetLength * 2; $i++) {
+        for ($i = 0; $i < $subsetLength * 2; $i++) {
             $rand = rand($index, $this->numSamples - 1);
             $samples[] = $this->samples[$rand];
             $targets[] = $this->targets[$rand];
@@ -138,7 +138,7 @@ 
     protected function initClassifiers()
     {
         $classifiers = [];
-        for ($i=0; $i<$this->numClassifier; $i++) {
+        for ($i = 0; $i < $this->numClassifier; $i++) {
             $ref = new \ReflectionClass($this->classifier);
             if ($this->classifierOptions) {
                 $obj = $ref->newInstanceArgs($this->classifierOptions);

src/Phpml/Classification/Ensemble/RandomForest.php

Unused Use Statements -2 removed lines

@@ -4,8 +4,6 @@
 namespace Phpml\Classification\Ensemble;
 
 use Phpml\Classification\Ensemble\Bagging;
-use Phpml\Classification\DecisionTree;
-use Phpml\Classification\NaiveBayes;
 
 class RandomForest extends Bagging
 {

Spacing +5 added lines, -5 removed lines

@@ -1,5 +1,5 @@ 
 <?php
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 
@@ -36,10 +36,10 @@ 
         list($subset, $targets) = parent::getRandomSubset($index);
 
         $features = [];
-        $featureCount = (int)ceil($this->featureSubsetRatio * $this->featureCount);
+        $featureCount = (int) ceil($this->featureSubsetRatio * $this->featureCount);
         while (count($features) < $featureCount) {
             $rand = rand(0, $this->featureCount - 1);
-            if (! in_array($rand, $features)) {
+            if (!in_array($rand, $features)) {
                 $features[] = $rand;
             }
         }
@@ -50,7 +50,7 @@ 
         foreach ($features as $colIndex) {
             $columns[] = array_column($subset, $colIndex);
         }
-        $subset= array_map(null, ...$columns);
+        $subset = array_map(null, ...$columns);
 
         return [$subset, $targets];
     }
@@ -62,7 +62,7 @@ 
     protected function predictSample(array $sample)
     {
         $predictions = [];
-        for ($i=0; $i<count($this->classifiers); $i++) {
+        for ($i = 0; $i < count($this->classifiers); $i++) {
             $samplePiece = [];
             foreach ($this->classifierColumns[$i] as $colIndex) {
                 $samplePiece[] = $sample[$colIndex];

src/Phpml/Classification/DecisionTree.php

Doc Comments +1 added lines, -1 removed lines

@@ -136,7 +136,7 @@
 
     /**
      * @param array $records
-     * @return DecisionTreeLeaf[]
+     * @return null|DecisionTreeLeaf
      */
     protected function getBestSplit($records)
     {

Indentation +1 added lines, -1 removed lines

@@ -275,7 +275,7 @@
             }
         } while ($node);
 
-		if ($node) {
+        if ($node) {
             return $node->classValue;
         }
         return $this->labels[0];