Use correct naming for iteration and epoch

app/Models/GradientDescentPerceptronTraining.php

@@ -4,6 +4,7 @@ namespace App\Models;
 
 use App\Events\PerceptronTrainingEnded;
 use App\Services\DataSetReader;
+use App\Services\IPerceptronIterationEventBuffer;
 use App\Services\ISynapticWeightsProvider;
 use App\Services\PerceptronIterationEventBuffer;
 
@@ -18,36 +19,36 @@ class GradientDescentPerceptronTraining extends NetworkTraining
     public function __construct(
         DataSetReader $datasetReader,
         protected float $learningRate,
-        int $maxIterations,
+        int $maxEpochs,
         protected ISynapticWeightsProvider $synapticWeightsProvider,
-        PerceptronIterationEventBuffer $iterationEventBuffer,
+        IPerceptronIterationEventBuffer $iterationEventBuffer,
         string $sessionId,
         string $trainingId,
         private float $minError,
     ) {
-        parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
+        parent::__construct($datasetReader, $maxEpochs, $iterationEventBuffer, $sessionId, $trainingId);
         $this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
     }
 
     public function start(): void
     {
-        $this->iteration = 0;
+        $this->epoch = 0;
         do {
             $this->epochError = 0;
-            $iterationErrorPerWeight = [];
-            $this->iteration++;
+            $epochCorrectorPerWeight = [];
+            $this->epoch++;
 
             while ($nextRow = $this->datasetReader->getRandomLine()) {
                 $inputs = array_slice($nextRow, 0, -1);
                 $correctOutput = (float) end($nextRow);
 
                 $iterationError = $this->iterationFunction($inputs, $correctOutput);
-                $this->epochError += (1 / 2) * (abs($iterationError) ** 2); // TDDO REMOVEME abs()
+                $this->epochError += ($iterationError ** 2) / 2;
 
                 // Store the iteration error for each weight
                 $inputs_with_bias = array_merge([1], $inputs); // Add bias input
                 foreach ($inputs_with_bias as $index => $input) {
-                    $iterationErrorPerWeight[$index][] = $iterationError * $input;
+                    $epochCorrectorPerWeight[$index][] = $iterationError * $input;
                 }
 
                 // Broadcast the training iteration event
@@ -57,14 +58,14 @@ class GradientDescentPerceptronTraining extends NetworkTraining
             // Synaptic weights correction after each epoch
             $synaptic_weights = $this->perceptron->getSynapticWeights();
             $new_weights = array_map(
-                fn($weight, $weightIndex) => $weight + $this->learningRate * array_sum($iterationErrorPerWeight[$weightIndex]),
+                fn($weight, $weightIndex) => $weight + $this->learningRate * array_sum($epochCorrectorPerWeight[$weightIndex]),
                 $synaptic_weights,
                 array_keys($synaptic_weights)
             );
             $this->perceptron->setSynapticWeights($new_weights);
 
             $this->datasetReader->reset(); // Reset the dataset for the next iteration
-        } while ($this->iteration < $this->maxIterations && !$this->stopCondition());
+        } while ($this->epoch < $this->maxEpochs && !$this->stopCondition());
 
         $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend