Gradient descent training + Added all dataset + graphs improvements

app/Http/Controllers/PerceptronController.php

@@ -2,14 +2,14 @@
 
 namespace App\Http\Controllers;
 
-use App\Models\SimplePerceptron;
-use App\Models\SimplePerceptronTraining;
+use App\Events\PerceptronInitialization;
+use App\Models\GradientDescentPerceptronTraining;
+use App\Models\SimpleBinaryPerceptronTraining;
 use App\Services\DataSetReader;
 use App\Services\ISynapticWeightsProvider;
 use App\Services\PerceptronIterationEventBuffer;
 use App\Services\ZeroSynapticWeights;
 use Illuminate\Http\Request;
-use Illuminate\Support\Facades\Log;
 
 class PerceptronController extends Controller
 {
@@ -18,29 +18,32 @@ class PerceptronController extends Controller
      */
     public function index(Request $request)
     {
-        $perceptronType = $request->query('type', 'simple');
+        $perceptronType = $request->query('type');
 
-        $learningRate = 0.1;
-        $maxIterations = 100;
+        $learningRate = 0.01;
+        $maxIterations = 200;
+        $minError = 0.6;
 
         switch ($perceptronType) {
             case 'simple':
                 $learningRate = 0.015;
-                $maxIterations = 100;
+                $maxIterations = 150;
                 break;
+            case 'gradientdescent':
+                $learningRate = 0.00003;
         }
 
         return inertia('PerceptronViewer', [
             'type' => $perceptronType,
             'sessionId' => session()->getId(),
-            'datasets' => $this->getDatasets(),
-            'minError' => 0.01,
+            'datasets' => $this->getDatasets($perceptronType),
+            'minError' => $minError,
             'learningRate' => $learningRate,
             'maxIterations' => $maxIterations,
         ]);
     }
 
-    private function getDatasets(): array
+    private function getDatasets(string $perceptronType): array
     {
         $dataSetsDirectory = public_path('data_sets');
         $files = scandir($dataSetsDirectory);
@@ -51,17 +54,44 @@ class PerceptronController extends Controller
                 $dataset['label'] = str_replace('.csv', '', $file);
                 $dataSetReader = new DataSetReader($dataSetsDirectory . '/' . $file);
                 $dataset['data'] = [];
-                foreach ($dataSetReader->lines as $line) {
-                    $dataset['data'][] = [
-                        'x' => $line[0],
-                        'y' => $line[1],
-                        'label' => $line[2],
-                    ];
+                switch (count($dataSetReader->lines[0])) {
+                    case 3:
+                        foreach ($dataSetReader->lines as $line) {
+                            $dataset['data'][] = [
+                                'x' => $line[0],
+                                'y' => $line[1],
+                                'label' => $line[2],
+                            ];
+                        }
+                        break;
+                    case 2:
+                        foreach ($dataSetReader->lines as $line) {
+                            $dataset['data'][] = [
+                                'x' => $line[0],
+                                'y' => $line[1],
+                                'label' => 1,
+                            ];
+                        }
+                        break;
+                    default:
+                        $dataset['data'] = null; // Not supported for viewing
+                        break;
                 }
 
                 switch ($dataset['label']) {
-                    case '2.9':
-                        $dataset['defaultLearningRate'] = 0.015;
+                    case 'logic_and_gradient':
+                        switch ($perceptronType) {
+                            case 'gradientdescent':
+                                $dataset['defaultLearningRate'] = 0.3;
+                                break;
+                        }
+                        break;
+                    case 'table_2_9':
+                        switch ($perceptronType) {
+                            case 'simple':
+                                $dataset['defaultLearningRate'] = 0.015;
+                                break;
+                        }
                         break;
                 }
                 $datasets[] = $dataset;
@@ -78,7 +108,7 @@ class PerceptronController extends Controller
 
     public function run(Request $request, ISynapticWeightsProvider $synapticWeightsProvider)
     {
-        $perceptronType = $request->input('type', 'simple');
+        $perceptronType = $request->input('type');
         $minError = $request->input('min_error', 0.01);
         $weightInitMethod = $request->input('weight_init_method', 'random');
         $dataSet = $request->input('dataset');
@@ -96,11 +126,12 @@ class PerceptronController extends Controller
         $iterationEventBuffer = new PerceptronIterationEventBuffer($sessionId, $trainingId);
 
         $networkTraining = match ($perceptronType) {
-            'simple' => new SimplePerceptronTraining($dataSetReader, $learningRate, $maxIterations, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId),
+            'simple' => new SimpleBinaryPerceptronTraining($dataSetReader, $learningRate, $maxIterations, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId),
+            'gradientdescent' => new GradientDescentPerceptronTraining($dataSetReader, $learningRate, $maxIterations, $synapticWeightsProvider, $iterationEventBuffer, $sessionId, $trainingId, $minError),
             default => null,
         };
 
-        event(new \App\Events\PerceptronInitialization($dataSetReader->lines, $networkTraining->activationFunction, $sessionId, $trainingId));
+        event(new PerceptronInitialization($dataSetReader->lines, $networkTraining->activationFunction, $sessionId, $trainingId));
 
         $networkTraining->start();
 

app/Models/ActivationsFunctions.php

@@ -5,6 +5,7 @@ namespace App\Models;
 enum ActivationsFunctions: string
 {
     case STEP = 'step';
+    case LINEAR = 'linear';
     case SIGMOID = 'sigmoid';
     case RELU = 'relu';
 }

app/Models/GradientDescentPerceptron.php

@@ -2,7 +2,7 @@
 
 namespace App\Models;
 
-class SimplePerceptron extends Perceptron {
+class GradientDescentPerceptron extends Perceptron {
 
     public function __construct(
         array $synaptic_weights,
@@ -10,9 +10,9 @@ class SimplePerceptron extends Perceptron {
         parent::__construct($synaptic_weights);
     }
 
-    public function activationFunction(float $weighted_sum): int
+    public function activationFunction(float $weighted_sum): float
     {
-        return $weighted_sum >= 0 ? 1 : 0;
+        return $weighted_sum;
     }
 
 }

app/Models/GradientDescentPerceptronTraining.php

@@ -0,0 +1,91 @@
+<?php
+
+namespace App\Models;
+
+use App\Events\PerceptronTrainingEnded;
+use App\Services\DataSetReader;
+use App\Services\ISynapticWeightsProvider;
+use App\Services\PerceptronIterationEventBuffer;
+
+class GradientDescentPerceptronTraining extends NetworkTraining
+{
+    private Perceptron $perceptron;
+
+    public ActivationsFunctions $activationFunction = ActivationsFunctions::LINEAR;
+
+    private float $epochError;
+
+    public function __construct(
+        DataSetReader $datasetReader,
+        protected float $learningRate,
+        int $maxIterations,
+        protected ISynapticWeightsProvider $synapticWeightsProvider,
+        PerceptronIterationEventBuffer $iterationEventBuffer,
+        string $sessionId,
+        string $trainingId,
+        private float $minError,
+    ) {
+        parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
+        $this->perceptron = new GradientDescentPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
+    }
+
+    public function start(): void
+    {
+        $this->iteration = 0;
+        do {
+            $this->epochError = 0;
+            $iterationErrorPerWeight = [];
+            $this->iteration++;
+
+            while ($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()
+
+                // 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;
+                }
+
+                // Broadcast the training iteration event
+                $this->addIterationToBuffer($iterationError, [[$this->perceptron->getSynapticWeights()]]);
+            }
+
+            // 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]),
+                $synaptic_weights,
+                array_keys($synaptic_weights)
+            );
+            $this->perceptron->setSynapticWeights($new_weights);
+
+            $this->datasetReader->reset(); // Reset the dataset for the next iteration
+        } while ($this->iteration < $this->maxIterations && !$this->stopCondition());
+
+        $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
+
+        $this->checkPassedMaxIterations($this->epochError);
+    }
+
+    protected function stopCondition(): bool
+    {
+        $condition = $this->epochError <= $this->minError && $this->perceptron->getSynapticWeights() !== [[0.0, 0.0, 0.0]];
+        if ($condition === true) {
+            event(new PerceptronTrainingEnded('Le perceptron à atteint l\'erreur minimale', $this->sessionId, $this->trainingId));
+        }
+        return $condition;
+    }
+
+    private function iterationFunction(array $inputs, int $correctOutput)
+    {
+        $output = $this->perceptron->test($inputs);
+
+        $error = $correctOutput - $output;
+
+        return $error;
+    }
+}

app/Models/Network.php

@@ -0,0 +1,8 @@
+<?php
+
+namespace App\Models;
+
+abstract class Network
+{
+
+}

app/Models/NetworkTraining.php

@@ -28,9 +28,14 @@ abstract class NetworkTraining
     abstract public function start() : void;
     abstract protected function stopCondition(): bool;
 
-    protected function checkPassedMaxIterations() {
+    protected function checkPassedMaxIterations(?float $finalError) {
         if ($this->iteration >= $this->maxIterations) {
-            event(new PerceptronTrainingEnded('Le nombre maximal d\'itérations a été atteint', $this->sessionId, $this->trainingId));
+            $message = 'Le nombre maximal d\'itérations a été atteint';
+            if ($finalError) {
+                $message .= " avec une erreur finale de $finalError";
+            }
+
+            event(new PerceptronTrainingEnded($message, $this->sessionId, $this->trainingId));
         }
     }
 

app/Models/Perceptron.php

@@ -12,7 +12,7 @@ abstract class Perceptron extends Model
         $this->synaptic_weights = $synaptic_weights;
     }
 
-    public function test(array $inputs): int
+    public function test(array $inputs): float
     {
         $inputs = array_merge([1], $inputs); // Add bias input
 
@@ -24,7 +24,7 @@ abstract class Perceptron extends Model
         return $this->activationFunction($weighted_sum);
     }
 
-    abstract public function activationFunction(float $weighted_sum): int;
+    abstract public function activationFunction(float $weighted_sum): float;
 
     public function getSynapticWeights(): array
     {

app/Models/SimpleBinaryPerceptron.php

@@ -0,0 +1,18 @@
+<?php
+
+namespace App\Models;
+
+class SimpleBinaryPerceptron extends Perceptron {
+
+    public function __construct(
+        array $synaptic_weights,
+    ) {
+        parent::__construct($synaptic_weights);
+    }
+
+    public function activationFunction(float $weighted_sum): float
+    {
+        return $weighted_sum >= 0.0 ? 1.0 : 0.0;
+    }
+
+}

app/Models/SimpleBinaryPerceptronTraining.php

@@ -6,9 +6,8 @@ use App\Events\PerceptronTrainingEnded;
 use App\Services\DataSetReader;
 use App\Services\ISynapticWeightsProvider;
 use App\Services\PerceptronIterationEventBuffer;
-use Illuminate\Support\Facades\Log;
 
-class SimplePerceptronTraining extends NetworkTraining
+class SimpleBinaryPerceptronTraining extends NetworkTraining
 {
     private Perceptron $perceptron;
     private int $iterationErrorCounter = 0;
@@ -27,7 +26,7 @@ class SimplePerceptronTraining extends NetworkTraining
         string $trainingId,
     ) {
         parent::__construct($datasetReader, $maxIterations, $iterationEventBuffer, $sessionId, $trainingId);
-        $this->perceptron = new SimplePerceptron($synapticWeightsProvider->generate(2));
+        $this->perceptron = new SimpleBinaryPerceptron($synapticWeightsProvider->generate($datasetReader->getInputSize()));
     }
 
     public function start(): void
@@ -40,13 +39,11 @@ class SimplePerceptronTraining extends NetworkTraining
 
             while ($nextRow = $this->datasetReader->getRandomLine()) {
                 $inputs = array_slice($nextRow, 0, -1);
-                $correctOutput = end($nextRow);
+                $correctOutput = (float) end($nextRow);
                 $correctOutput = $correctOutput > 0 ? 1 : 0; // Modify labels for non binary datasets
 
                 $error = $this->iterationFunction($inputs, $correctOutput);
 
-                $error = abs($error); // Use absolute error
-
                 // Broadcast the training iteration event
                 $this->addIterationToBuffer($error, [[$this->perceptron->getSynapticWeights()]]);
             }
@@ -55,7 +52,7 @@ class SimplePerceptronTraining extends NetworkTraining
 
         $this->iterationEventBuffer->flush(); // Ensure all iterations are sent to the frontend
 
-        $this->checkPassedMaxIterations();
+        $this->checkPassedMaxIterations(null);
     }
 
     protected function stopCondition(): bool

app/Services/CsvReader.php

@@ -4,7 +4,7 @@ namespace App\Services;
 
 class CsvReader {
     private $file;
-    private array $headers;
+    // private array $headers;
 
     public array $lines = [];
 
@@ -17,7 +17,7 @@ class CsvReader {
             throw new \RuntimeException("Failed to open file: " . $filename);
         }
 
-        $this->headers = $this->readNextLine();
+        // $this->headers = $this->readNextLine();
     }
 
     public function readNextLine(): ?array

app/Services/DataSetReader.php

@@ -20,7 +20,17 @@ class DataSetReader {
     private function readEntireFile(CsvReader $reader): void
     {
         while ($line = $reader->readNextLine()) {
-            $this->lines[] = $line;
+            $newLine = [];
+            foreach ($line as $value) { // Transform to float
+                $newLine[] = (float) $value;
+            }
+
+            // if the dataset is for regression, we add a fake label of 0
+            if (count($newLine) === 2) {
+                $newLine[] = 0.0;
+            }
+
+            $this->lines[] = $newLine;
         }
     }
 
@@ -31,12 +41,21 @@ class DataSetReader {
         }
         $randomNumber = array_rand($this->currentLines);
         $randomLine = $this->currentLines[$randomNumber];
+
         // Remove the line from the current lines to avoid repetition
         unset($this->currentLines[$randomNumber]);
+
+        // Remember the index of the last read line in the full list
         $this->lastReadLineIndex = array_search($randomLine, $this->lines, true);
+
         return $randomLine;
     }
 
+    public function getInputSize(): int
+    {
+        return count($this->lines[0]) - 1; // Don't count the label
+    }
+
     public function reset(): void
     {
         $this->currentLines = $this->lines;

public/data_sets/2.9.csv

@@ -1,22 +0,0 @@
-x_1, x_2, d
-1, 6, 1
-7, 9, -1
-1, 9, 1
-7, 10, -1
-2, 5, -1
-2, 7, 1
-2, 8, 1
-6, 8, -1
-6, 9, -1
-3, 5, -1
-3, 6, -1
-3, 8, 1
-3, 9, 1
-5, 7, -1
-5, 8, -1
-5, 10, 1
-5, 11, 1
-4, 6, -1
-4, 7, -1
-4, 9, 1
-4, 10, 1

public/data_sets/logic_and.csv

@@ -1,4 +1,3 @@
-x_1, x_2, d
 0, 0, 0
 0, 1, 0
 1, 0, 0

public/data_sets/logic_and_gradient.csv

@@ -0,0 +1,4 @@
+0, 0, -1
+0, 1, -1
+1, 0, -1
+1, 1, 1

public/data_sets/logic_xor.csv

@@ -1,4 +1,3 @@
-x_1, x_2, d
 0, 0, 1
 0, 1, 0
 1, 0, 0

public/data_sets/table_2_10.csv

@@ -0,0 +1,23 @@
+1,2,1
+1,4,-1
+1,5,1
+7,5,-1
+7,6,-1
+2,1,-1
+2,3,1
+2,4,1
+6,2,1
+6,4,-1
+6,5,-1
+3,1,-1
+3,2,-1
+3,4,1
+3,5,1
+5,3,-1
+5,4,-1
+5,6,1
+5,7,1
+4,2,-1
+4,3,1
+4,5,1
+4,6,1

public/data_sets/table_2_11.csv

@@ -0,0 +1,30 @@
+10,4.4
+14,5.6
+12,4.6
+18,6.1
+16,6.0
+14,7.0
+22,6.8
+28,10.6
+26,11.0
+16,7.6
+23,10.8
+25,10.0
+20,6.5
+20,8.2
+24,8.8
+12,5.5
+15,5.0
+18,8.0
+14,7.8
+26,9.0
+25,9.4
+17,8.5
+12,6.4
+20,7.5
+23,9.0
+22,8.1
+26,8.2
+22,10.0
+18,9.1
+21,9.0

public/data_sets/table_2_9.csv

@@ -0,0 +1,21 @@
+1,6,1
+7,9,-1
+1,9,1
+7,10,-1
+2,5,-1
+2,7,1
+2,8,1
+6,8,-1
+6,9,-1
+3,5,-1
+3,6,-1
+3,8,1
+3,9,1
+5,7,-1
+5,8,-1
+5,10,1
+5,11,1
+4,6,-1
+4,7,-1
+4,9,1
+4,10,1

public/data_sets/table_3_1.csv

@@ -0,0 +1,150 @@
+2.8,1.9,-1,-1,1
+2.9,1.8,-1,-1,1
+2.2,1.5,-1,-1,1
+1.3,5.6,-1,1,-1
+-1.2,1.6,1,-1,-1
+2.5,1.7,-1,-1,1
+3.1,2.3,-1,-1,1
+2.8,2.4,-1,-1,1
+-1.2,1.5,1,-1,-1
+1.4,6.1,-1,1,-1
+-1.2,1.3,1,-1,-1
+3.1,1.8,-1,-1,1
+3.3,2.5,-1,-1,1
+3.4,2.3,-1,-1,1
+1.5,5.9,-1,1,-1
+1.3,5.6,-1,1,-1
+-1.2,1,1,-1,-1
+3,2.1,-1,-1,1
+1.4,5.2,-1,1,-1
+1.2,5.5,-1,1,-1
+1.4,6.7,-1,1,-1
+-1.3,1.7,1,-1,-1
+1,5.7,-1,1,-1
+2.6,1.4,-1,-1,1
+1.6,6,-1,1,-1
+1.2,5.8,-1,1,-1
+1.4,6.1,-1,1,-1
+1.3,5.7,-1,1,-1
+-1.2,1.4,1,-1,-1
+1,5.5,-1,1,-1
+3.1,2.1,-1,-1,1
+-1.4,1.7,1,-1,-1
+1.6,6.3,-1,1,-1
+-1.2,1.4,1,-1,-1
+2.7,1.9,-1,-1,1
+1.1,5.5,-1,1,-1
+3,1.8,-1,-1,1
+3.8,2,-1,-1,1
+2.8,2.1,-1,-1,1
+1,5,-1,1,-1
+2.8,2,-1,-1,1
+-1.2,1.6,1,-1,-1
+1.3,6.6,-1,1,-1
+1.6,6,-1,1,-1
+3,1.6,-1,-1,1
+-1.1,1.1,1,-1,-1
+2.9,1.8,-1,-1,1
+3,1.8,-1,-1,1
+-1.2,1.4,1,-1,-1
+1,5.8,-1,1,-1
+1.2,5.7,-1,1,-1
+2.8,1.5,-1,-1,1
+-1.4,1.6,1,-1,-1
+-1.2,1.4,1,-1,-1
+2.8,2.2,-1,-1,1
+-1.5,1.7,1,-1,-1
+1,4.9,-1,1,-1
+1.3,5.7,-1,1,-1
+3.2,2.3,-1,-1,1
+-1.3,1.5,1,-1,-1
+-1.2,1.2,1,-1,-1
+-1.2,1.6,1,-1,-1
+3,2.1,-1,-1,1
+-1.4,1.5,1,-1,-1
+1.3,5.5,-1,1,-1
+3.3,2.5,-1,-1,1
+3.1,2.4,-1,-1,1
+1.8,5.9,-1,1,-1
+2.7,1.9,-1,-1,1
+1.5,6.3,-1,1,-1
+-1.3,1.4,1,-1,-1
+1,5,-1,1,-1
+3.2,2.3,-1,-1,1
+-1.3,1.4,1,-1,-1
+3,2.1,-1,-1,1
+3.2,2,-1,-1,1
+1.3,6.3,-1,1,-1
+1.4,7,-1,1,-1
+-1.2,1.7,1,-1,-1
+1.4,6.6,-1,1,-1
+1.2,5.8,-1,1,-1
+3,2,-1,-1,1
+-1.2,1.6,1,-1,-1
+1.5,6.2,-1,1,-1
+1.5,6.4,-1,1,-1
+-1.2,1.9,1,-1,-1
+3.2,2.3,-1,-1,1
+-1.2,1.5,1,-1,-1
+1.5,5.4,-1,1,-1
+1.5,6,-1,1,-1
+1.5,6.9,-1,1,-1
+-1.4,1.5,1,-1,-1
+1.3,6.4,-1,1,-1
+2.8,2,-1,-1,1
+-1.2,1.5,1,-1,-1
+-1.1,1.5,1,-1,-1
+3.6,2.5,-1,-1,1
+1.1,5.1,-1,1,-1
+-1.1,1.5,1,-1,-1
+-1.2,1.5,1,-1,-1
+3.4,2.4,-1,-1,1
+-1.3,1.3,1,-1,-1
+3,2.3,-1,-1,1
+-1.1,1.5,1,-1,-1
+1.1,5.6,-1,1,-1
+1.3,5.6,-1,1,-1
+-1.2,1.5,1,-1,-1
+-1.2,1.3,1,-1,-1
+1.7,6.7,-1,1,-1
+-1.2,1.3,1,-1,-1
+-1.4,1.3,1,-1,-1
+2.5,1.8,-1,-1,1
+-1.4,1.5,1,-1,-1
+1.5,6.5,-1,1,-1
+2.6,2.3,-1,-1,1
+-1.2,1.4,1,-1,-1
+1.5,5.6,-1,1,-1
+1.3,5.7,-1,1,-1
+1.2,6.1,-1,1,-1
+3,2.2,-1,-1,1
+3,1.8,-1,-1,1
+-1.1,1.4,1,-1,-1
+1.4,6.8,-1,1,-1
+-1.6,1.6,1,-1,-1
+-1.2,1.4,1,-1,-1
+3.2,1.8,-1,-1,1
+-1.2,1.5,1,-1,-1
+2.7,1.8,-1,-1,1
+-1.3,1.4,1,-1,-1
+1.3,6.2,-1,1,-1
+-1.3,1.3,1,-1,-1
+3,1.8,-1,-1,1
+2.7,1.9,-1,-1,1
+-1.2,1.4,1,-1,-1
+-1.2,1.2,1,-1,-1
+1.5,6.7,-1,1,-1
+2.5,1.9,-1,-1,1
+3.3,2.1,-1,-1,1
+2.8,1.8,-1,-1,1
+-1.2,1.3,1,-1,-1
+3.8,2.2,-1,-1,1
+2.5,2,-1,-1,1
+1.3,6.1,-1,1,-1
+-1.2,1.4,1,-1,-1
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public/data_sets/table_3_5.csv

@@ -0,0 +1,4 @@
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public/data_sets/table_4_12.csv

@@ -0,0 +1,100 @@
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public/data_sets/table_4_14.csv

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+0.14,0.29,0.0,1.0,0.0
+1.09,0.68,0.0,1.0,0.0

public/data_sets/table_4_17.csv

@@ -0,0 +1,120 @@
+-0.4,-1.32
+1.7,-0.04
+0.53,-0.07
+-1.9,1.09
+0.53,0.12
+1.85,0.17
+-1.35,-0.46
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+-0.67,-0.71
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+1.34,0.07
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+-1.9,0.84
+0.39,-0.71
+-0.71,-1.32
+1.82,-0.1
+0.79,0.18
+1.65,0.39
+-1.65,1
+1.01,0.03
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+-1.64,0.98
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+-0.68,-1.04
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+-1.79,1.09
+-1.39,1.17
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+-0.28,-1.09
+-1.59,1.14
+-0.07,-0.75
+-0.81,-0.43
+-0.5,-1.1
+-1.84,1.54
+-0.84,-0.84
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+-1.59,1.56
+-1.12,-0.79
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+-0.87,-1.07
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+-1.26,0.34
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+0,-0.79
+-1.07,0.1
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+-1.67,1.35
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+-0.07,-1.01
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+-1.64,1.39
+-0.67,-0.82
+-0.29,-1.03
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+-1.4,0.1
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+-0.21,-1.21
+-1.45,0.98
+1.2,0.45
+-0.28,-1.1
+0.09,-0.26
+-1.32,0.5
+1.12,0.34
+-1.53,0.54
+-1.65,1.64
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+0.7,0
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+-1.29,0
+-1.73,0.9
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+-1.14,-0.14
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+-0.23,-0.89
+-0.37,-1.34
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+-1.04,0.32
+-1.56,0.85
+1.57,0.42
+-1.26,0.76
+-1.81,1.25

resources/js/components/LinkHeader.vue

@@ -11,9 +11,9 @@ const links = [
         data: { type: 'simple' },
     },
     {
-        name: 'Perceptron Complex',
+        name: 'Descente du gradient',
         href: '/perceptron',
-        data: { type: 'complex' },
+        data: { type: 'gradientdescent' },
     },
 ];
 

resources/js/components/PerceptronDecisionGraph.vue

@@ -7,7 +7,7 @@ import type {
 } from 'chart.js';
 import { computed } from 'vue';
 import { Chart } from 'vue-chartjs';
-import { colors } from '@/types/graphs';
+import { colors, gridColor, gridColorBold } from '@/types/graphs';
 import type { Iteration } from '@/types/perceptron';
 
 const props = defineProps<{
@@ -157,10 +157,28 @@ function getPerceptronDecisionBoundaryDataset(
                 x: {
                     type: 'linear',
                     position: 'bottom',
+                    grid: {
+                        color: function (context) {
+                            if (context.tick.value == 0) {
+                                return gridColorBold;
+                            } 
+
+                            return gridColor;
+                        },
+                    },
                 },
                 y: {
                     type: 'linear',
                     position: 'left',
+                    grid: {
+                        color: function (context) {
+                            if (context.tick.value == 0) {
+                                return gridColorBold;
+                            } 
+
+                            return gridColor;
+                        },
+                    },
                 },
             },
         }"

resources/js/components/PerceptronIterationsErrorsGraph.vue

@@ -1,7 +1,7 @@
 <script setup lang="ts">
 import type { ChartData } from 'chart.js';
 import { Bar } from 'vue-chartjs';
-import { colors } from '@/types/graphs';
+import { colors, gridColor, gridColorBold } from '@/types/graphs';
 import type { Iteration } from '@/types/perceptron';
 
 const props = defineProps<{
@@ -17,6 +17,7 @@ function getPerceptronErrorsPerIteration(): ChartData<
 >[] {
     const datasets: ChartData<'bar', (number | [number, number] | null)[]>[] =
         [];
+    const epochAverageError: number[] = [];
 
     const backgroundColors = colors;
 
@@ -27,6 +28,7 @@ function getPerceptronErrorsPerIteration(): ChartData<
             dataset = {
                 label: exampleLabel,
                 data: [],
+                order: 1,
                 backgroundColor:
                     backgroundColors[
                         iteration.exampleIndex % backgroundColors.length
@@ -35,6 +37,11 @@ function getPerceptronErrorsPerIteration(): ChartData<
             datasets.push(dataset);
         }
         dataset.data.push(iteration.error);
+
+        // Epoch error
+        epochAverageError[iteration.iteration - 1] =
+            (epochAverageError[iteration.iteration - 1] || 0) +
+            iteration.error ** 2 / 2;
     });
 
     // Sort dataset by label (Exemple 0, Exemple 1, ...)
@@ -44,6 +51,23 @@ function getPerceptronErrorsPerIteration(): ChartData<
         return aIndex - bIndex;
     });
 
+    // Epoch error
+    const epochErrorDataset = {
+        type: 'line',
+        label: "Erreur de l'époque",
+        data: [],
+        backgroundColor: '#fff',
+        borderColor: '#fff',
+        order: 0,
+        tension: 0.3,
+    };
+
+    epochAverageError.forEach((error) => {
+        epochErrorDataset.data.push(error);
+    });
+
+    datasets.push(epochErrorDataset);
+
     return datasets;
 }
 </script>
@@ -68,6 +92,15 @@ function getPerceptronErrorsPerIteration(): ChartData<
                 y: {
                     stacked: true,
                     beginAtZero: true,
+                    grid: {
+                        color: function (context) {
+                            if (context.tick.value == 0) {
+                                return gridColorBold;
+                            } 
+
+                            return gridColor;
+                        },
+                    },
                 },
             },
         }"

resources/js/components/PerceptronSetup.vue

@@ -73,10 +73,10 @@ function startTraining() {
         },
         credentials: 'same-origin',
         body: JSON.stringify({
-            type: 'simple',
+            type: props.type,
             dataset: selectedDatasetCopy.value,
             weight_init_method: selectedMethod.value,
-            min_error: 0.01,
+            min_error: minError.value,
             learning_rate: learningRate.value,
             session_id: props.sessionId,
             training_id: trainingId.value,

resources/js/pages/PerceptronViewer.vue

@@ -155,6 +155,8 @@ function getActivationFunction(type: string): (x: number) => number {
             return (x) => 1 / (1 + Math.exp(-x));
         case 'tanh':
             return (x) => Math.tanh(x);
+        case 'linear':
+            return (x) => x;
         default:
             return (x) => x; // Identity function as fallback
     }

resources/js/types/graphs.ts

@@ -32,3 +32,6 @@ export const colors = [
                             '#DC143C',
                             '#00FF00',
                         ] as const;
+
+export const gridColor = '#444';
+export const gridColorBold = '#999';