php-ai / php-ml

src/Phpml/Classification/DecisionTree.php

Spacing +9 added lines, -9 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification;
 
@@ -114,7 +114,7 @@ 
     {
         $types = [];
         $featureCount = count($samples[0]);
-        for ($i=0; $i < $featureCount; $i++) {
+        for ($i = 0; $i < $featureCount; $i++) {
             $values = array_column($samples, $i);
             $isCategorical = self::isCategoricalColumn($values);
             $types[] = $isCategorical ? self::NOMINAL : self::CONTINUOUS;
@@ -140,7 +140,7 @@ 
         // otherwise group the records so that we can classify the leaf
         // in case maximum depth is reached
         $leftRecords = [];
-        $rightRecords= [];
+        $rightRecords = [];
         $remainingTargets = [];
         $prevRecord = null;
         $allSame = true;
@@ -158,12 +158,12 @@ 
             if ($split->evaluate($record)) {
                 $leftRecords[] = $recordNo;
             } else {
-                $rightRecords[]= $recordNo;
+                $rightRecords[] = $recordNo;
             }
 
             // Group remaining targets
             $target = $this->targets[$recordNo];
-            if (! array_key_exists($target, $remainingTargets)) {
+            if (!array_key_exists($target, $remainingTargets)) {
                 $remainingTargets[$target] = 1;
             } else {
                 $remainingTargets[$target]++;
@@ -179,7 +179,7 @@ 
                 $split->leftLeaf = $this->getSplitLeaf($leftRecords, $depth + 1);
             }
             if ($rightRecords) {
-                $split->rightLeaf= $this->getSplitLeaf($rightRecords, $depth + 1);
+                $split->rightLeaf = $this->getSplitLeaf($rightRecords, $depth + 1);
             }
         }
 
@@ -251,7 +251,7 @@ 
     protected function getSelectedFeatures() : array
     {
         $allFeatures = range(0, $this->featureCount - 1);
-        if ($this->numUsableFeatures === 0 && ! $this->selectedFeatures) {
+        if ($this->numUsableFeatures === 0 && !$this->selectedFeatures) {
             return $allFeatures;
         }
 
@@ -288,7 +288,7 @@ 
             $countMatrix[$label][$rowIndex]++;
         }
         $giniParts = [0, 0];
-        for ($i=0; $i<=1; $i++) {
+        for ($i = 0; $i <= 1; $i++) {
             $part = 0;
             $sum = array_sum(array_column($countMatrix, $i));
             if ($sum > 0) {
@@ -311,7 +311,7 @@ 
         // Detect and convert continuous data column values into
         // discrete values by using the median as a threshold value
         $columns = [];
-        for ($i=0; $i<$this->featureCount; $i++) {
+        for ($i = 0; $i < $this->featureCount; $i++) {
             $values = array_column($samples, $i);
             if ($this->columnTypes[$i] == self::CONTINUOUS) {
                 $median = Mean::median($values);