php-ai / php-ml

src/Phpml/Clustering/FuzzyCMeans.php

Spacing +2 added lines, -4 removed lines

@@ -1,5 +1,5 @@ 
 <?php
-<<<<<<< HEAD
+<< << <<< HEAD
 =======
 
 >>>>>>> refs/remotes/php-ai/master
@@ -241,6 +241,4 @@ 
         foreach ($this->clusters as $cluster) {
             $grouped[] = $cluster->getPoints();
         }
-        return $grouped;
-    }
-}
+        return $grouped
\ No newline at end of file

src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php

Spacing +3 added lines, -5 removed lines

@@ -1,5 +1,5 @@ 
 <?php
-<<<<<<< HEAD
+<< << <<< HEAD
 =======
 
 >>>>>>> refs/remotes/php-ai/master
@@ -64,7 +64,7 @@ 
      */
     public function evaluate($record)
     {
-        $recordField = $record[$this->columnIndex];
+        $recordField = $record[$this - >columnIndex];
         if (preg_match("/^([<>=]{1,2})\s*(.*)/", $this->value, $matches)) {
             $op = $matches[1];
             $value= floatval($matches[2]);
@@ -105,6 +105,4 @@ 
             $str .= '</tr>';
         }
         $str .= '</table>';
-        return $str;
-    }
-}
+        return $str
\ No newline at end of file

src/Phpml/Classification/DecisionTree.php

Spacing +3 added lines, -6 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification;
 
@@ -19,7 +19,7 @@ 
     /**
      * @var array
      */
-<<<<<<< HEAD
+<< << <<< HEAD
     private $samples = array();
 =======
     private $samples = [];
@@ -306,7 +306,4 @@ 
         }
         return $this->labels[0];
 =======
-        return $node->classValue;
->>>>>>> refs/remotes/php-ai/master
-    }
-}
+        return $node->classValue
\ No newline at end of file

src/Phpml/Classification/Ensemble/RandomForest.php

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/Ensemble/Bagging.php

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/NaiveBayes.php

Spacing +6 added lines, -8 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification;
 
@@ -13,8 +13,8 @@ 
 {
     use Trainable, Predictable;
 
-    const CONTINUOS    = 1;
-    const NOMINAL    = 2;
+    const CONTINUOS = 1;
+    const NOMINAL = 2;
     const EPSILON = 1e-10;
 
     /**
@@ -25,7 +25,7 @@ 
     /**
      * @var array
      */
-    private $mean= [];
+    private $mean = [];
 
     /**
      * @var array
@@ -68,7 +68,7 @@ 
         $this->sampleCount = count($this->samples);
         $this->featureCount = count($this->samples[0]);
 
-<<<<<<< HEAD
+<< << <<< HEAD
         $labelCounts = array_count_values($targets);
 =======
         $labelCounts = array_count_values($this->targets);
@@ -187,6 +187,4 @@ 
         }
         arsort($predictions, SORT_NUMERIC);
         reset($predictions);
-        return key($predictions);
-    }
-}
+        return key($predictions
\ No newline at end of file