php-ai / php-ml

src/Phpml/Classification/DecisionTree.php

Doc Comments +2 added lines, -4 removed lines

@@ -184,7 +184,7 @@ 
 
     /**
      * @param array $records
-     * @return DecisionTreeLeaf[]
+     * @return null|DecisionTreeLeaf
      */
     protected function getBestSplit($records)
     {
@@ -377,7 +377,7 @@ 
     /**
      * Used to set predefined features to consider while deciding which column to use for a split
      *
-     * @param array $selectedFeatures
+     * @param integer[] $selectedFeatures
      */
     protected function setSelectedFeatures(array $selectedFeatures)
     {
@@ -415,7 +415,6 @@ 
      * each column in the given dataset. The importance values are
      * normalized and their total makes 1.<br/>
      *
-     * @param array $labels
      * @return array
      */
     public function getFeatureImportances()
@@ -455,7 +454,6 @@ 
      *
      * @param int $column
      * @param DecisionTreeLeaf
-     * @param array $collected
      *
      * @return array
      */

src/Phpml/Classification/Linear/Adaline.php

Unused Use Statements -3 removed lines

@@ -4,9 +4,6 @@
 
 namespace Phpml\Classification\Linear;
 
-use Phpml\Helper\Predictable;
-use Phpml\Helper\Trainable;
-use Phpml\Classification\Classifier;
 use Phpml\Classification\Linear\Perceptron;
 
 class Adaline extends Perceptron

Spacing +5 added lines, -5 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -15,12 +15,12 @@ 
     /**
      * Batch training is the default Adaline training algorithm
      */
-    const BATCH_TRAINING    = 1;
+    const BATCH_TRAINING = 1;
 
     /**
      * Online training: Stochastic gradient descent learning
      */
-    const ONLINE_TRAINING    = 2;
+    const ONLINE_TRAINING = 2;
 
     /**
      * The function whose result will be used to calculate the network error
@@ -52,7 +52,7 @@ 
     public function __construct(float $learningRate = 0.001, int $maxIterations = 1000,
         bool $normalizeInputs = true, int $trainingType = self::BATCH_TRAINING)
     {
-        if (! in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING])) {
+        if (!in_array($trainingType, [self::BATCH_TRAINING, self::ONLINE_TRAINING])) {
             throw new \Exception("Adaline can only be trained with batch and online/stochastic gradient descent algorithm");
         }
 
@@ -104,7 +104,7 @@ 
     protected function updateWeights(array $updates)
     {
         // Updates all weights at once
-        for ($i=0; $i <= $this->featureCount; $i++) {
+        for ($i = 0; $i <= $this->featureCount; $i++) {
             if ($i == 0) {
                 $this->weights[0] += $this->learningRate * array_sum($updates);
             } else {

src/Phpml/Classification/Linear/DecisionStump.php

Doc Comments +2 added lines, -2 removed lines

@@ -158,8 +158,8 @@
      * @param string $operator
      * @param array $values
      * @param array $targets
-     * @param mixed $leftLabel
-     * @param mixed $rightLabel
+     * @param string $leftLabel
+     * @param string $rightLabel
      */
     protected function calculateErrorRate(float $threshold, string $operator, array $values, array $targets, $leftLabel, $rightLabel)
     {

Unused Use Statements -2 removed lines

@@ -6,9 +6,7 @@
 
 use Phpml\Helper\Predictable;
 use Phpml\Helper\Trainable;
-use Phpml\Classification\Classifier;
 use Phpml\Classification\DecisionTree;
-use Phpml\Classification\DecisionTree\DecisionTreeLeaf;
 
 class DecisionStump extends DecisionTree
 {

Spacing +4 added lines, -4 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Linear;
 
@@ -122,7 +122,7 @@ 
         $stepSize = ($maxValue - $minValue) / 100.0;
 
         $leftLabel = $this->tree->leftLeaf->classValue;
-        $rightLabel= $this->tree->rightLeaf->classValue;
+        $rightLabel = $this->tree->rightLeaf->classValue;
 
         $bestOperator = $this->tree->operator;
         $bestThreshold = $this->tree->numericValue;
@@ -130,8 +130,8 @@ 
                 $bestThreshold, $bestOperator, $values, $targets, $leftLabel, $rightLabel);
 
         foreach (['<=', '>'] as $operator) {
-            for ($step = $minValue; $step <= $maxValue; $step+= $stepSize) {
-                $threshold = (float)$step;
+            for ($step = $minValue; $step <= $maxValue; $step += $stepSize) {
+                $threshold = (float) $step;
                 $errorRate = $this->calculateErrorRate(
                     $threshold, $operator, $values, $targets, $leftLabel, $rightLabel);
 

src/Phpml/Classification/Linear/Perceptron.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;
 
@@ -138,7 +138,7 @@ 
                 // Update bias
                 $this->weights[0] += $update * $this->learningRate; // Bias
                 // Update other weights
-                for ($i=1; $i <= $this->featureCount; $i++) {
+                for ($i = 1; $i <= $this->featureCount; $i++) {
                     $this->weights[$i] += $update * $sample[$i - 1] * $this->learningRate;
                 }
             }
@@ -190,6 +190,6 @@ 
 
         $predictedClass = $this->outputClass($sample);
 
-        return $this->labels[ $predictedClass ];
+        return $this->labels[$predictedClass];
     }
 }

src/Phpml/Classification/Ensemble/AdaBoost.php

Spacing +3 added lines, -3 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\Ensemble;
 
@@ -122,7 +122,7 @@ 
         //  classifiers as well
         $minErrorRate = 1.0;
         $bestClassifier = null;
-        for ($i=0; $i < $this->featureCount; $i++) {
+        for ($i = 0; $i < $this->featureCount; $i++) {
             $stump = new DecisionStump($i);
             $stump->setSampleWeights($this->weights);
             $stump->train($this->samples, $this->targets);
@@ -185,6 +185,6 @@ 
             $sum += $h * $alpha;
         }
 
-        return $this->labels[ $sum > 0 ? 1 : -1];
+        return $this->labels[$sum > 0 ? 1 : -1];
     }
 }

src/Phpml/Classification/DecisionTree/DecisionTreeLeaf.php

Spacing +14 added lines, -14 removed lines

@@ -1,6 +1,6 @@ 
 <?php
 
-declare(strict_types=1);
+declare(strict_types = 1);
 
 namespace Phpml\Classification\DecisionTree;
 
@@ -34,7 +34,7 @@ 
     /**
      * @var DecisionTreeLeaf
      */
-    public $rightLeaf= null;
+    public $rightLeaf = null;
 
     /**
      * @var array
@@ -79,7 +79,7 @@ 
 
         if ($this->isContinuous) {
             $op = $this->operator;
-            $value= $this->numericValue;
+            $value = $this->numericValue;
             $recordField = strval($recordField);
             eval("\$result = $recordField $op $value;");
             return $result;
@@ -100,16 +100,16 @@ 
             return 0.0;
         }
 
-        $nodeSampleCount = (float)count($this->records);
+        $nodeSampleCount = (float) count($this->records);
         $iT = $this->giniIndex;
 
         if ($this->leftLeaf) {
-            $pL = count($this->leftLeaf->records)/$nodeSampleCount;
+            $pL = count($this->leftLeaf->records) / $nodeSampleCount;
             $iT -= $pL * $this->leftLeaf->giniIndex;
         }
 
         if ($this->rightLeaf) {
-            $pR = count($this->rightLeaf->records)/$nodeSampleCount;
+            $pR = count($this->rightLeaf->records) / $nodeSampleCount;
             $iT -= $pR * $this->rightLeaf->giniIndex;
         }
 
@@ -133,25 +133,25 @@ 
             } else {
                 $col = "col_$this->columnIndex";
             }
-            if (! preg_match("/^[<>=]{1,2}/", $value)) {
+            if (!preg_match("/^[<>=]{1,2}/", $value)) {
                 $value = "=$value";
             }
-            $value = "<b>$col $value</b><br>Gini: ". number_format($this->giniIndex, 2);
+            $value = "<b>$col $value</b><br>Gini: ".number_format($this->giniIndex, 2);
         }
         $str = "<table ><tr><td colspan=3 align=center style='border:1px solid;'>
 				$value</td></tr>";
         if ($this->leftLeaf || $this->rightLeaf) {
-            $str .='<tr>';
+            $str .= '<tr>';
             if ($this->leftLeaf) {
-                $str .="<td valign=top><b>| Yes</b><br>" . $this->leftLeaf->getHTML($columnNames) . "</td>";
+                $str .= "<td valign=top><b>| Yes</b><br>".$this->leftLeaf->getHTML($columnNames)."</td>";
             } else {
-                $str .='<td></td>';
+                $str .= '<td></td>';
             }
-            $str .='<td>&nbsp;</td>';
+            $str .= '<td>&nbsp;</td>';
             if ($this->rightLeaf) {
-                $str .="<td valign=top align=right><b>No |</b><br>" . $this->rightLeaf->getHTML($columnNames) . "</td>";
+                $str .= "<td valign=top align=right><b>No |</b><br>".$this->rightLeaf->getHTML($columnNames)."</td>";
             } else {
-                $str .='<td></td>';
+                $str .= '<td></td>';
             }
             $str .= '</tr>';
         }