php-ai / php-ml

src/Phpml/Helper/Optimizer/StochasticGD.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Helper\Optimizer;
 
@@ -240,7 +240,7 @@ 
     {
         // Check for early stop: No change larger than threshold (default 1e-5)
         $diff = array_map(
-            function ($w1, $w2) {
+            function($w1, $w2) {
                 return abs($w1 - $w2) > $this->threshold ? 1 : 0;
             },
             $oldTheta,

src/Phpml/Helper/Optimizer/GD.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Helper\Optimizer;
 

src/Phpml/Clustering/FuzzyCMeans.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Clustering;
 
@@ -101,7 +101,7 @@ 
                 $total += $val;
             }
 
-            $this->membership[] = array_map(function ($val) use ($total) {
+            $this->membership[] = array_map(function($val) use ($total) {
                 return $val / $total;
             }, $row);
         }

src/Phpml/Classification/Ensemble/RandomForest.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 

src/Phpml/Classification/Ensemble/AdaBoost.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 

src/Phpml/Classification/Linear/Adaline.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -64,7 +64,7 @@ 
     protected function runTraining(array $samples, array $targets)
     {
         // The cost function is the sum of squares
-        $callback = function ($weights, $sample, $target) {
+        $callback = function($weights, $sample, $target) {
             $this->weights = $weights;
 
             $output = $this->output($sample);

src/Phpml/Classification/Linear/LogisticRegression.php

Spacing +3 added lines, -3 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -193,7 +193,7 @@ 
                  * The gradient of the cost function to be used with gradient descent:
                  *		∇J(x) = -(y - h(x)) = (h(x) - y)
                  */
-                $callback = function ($weights, $sample, $y) use ($penalty) {
+                $callback = function($weights, $sample, $y) use ($penalty) {
                     $this->weights = $weights;
                     $hX = $this->output($sample);
 
@@ -224,7 +224,7 @@ 
                  * The gradient of the cost function:
                  *		∇J(x) = -(h(x) - y) . h(x) . (1 - h(x))
                  */
-                $callback = function ($weights, $sample, $y) use ($penalty) {
+                $callback = function($weights, $sample, $y) use ($penalty) {
                     $this->weights = $weights;
                     $hX = $this->output($sample);
 

src/Phpml/DimensionReduction/LDA.php

Spacing +2 added lines, -2 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;
 
@@ -146,7 +146,7 @@ 
 
         // Calculate overall mean of the dataset for each column
         $numElements = array_sum($counts);
-        $map = function ($el) use ($numElements) {
+        $map = function($el) use ($numElements) {
             return $el / $numElements;
         };
         $this->overallMean = array_map($map, $overallMean);

src/Phpml/DimensionReduction/EigenTransformerBase.php

Spacing +1 added lines, -1 removed lines

@@ -1,6 +1,6 @@
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\DimensionReduction;