batuhan-basoglu/Classification-of-Image-Data-with-MLP-and-CNN
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Added the comments to the graph code.

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Batuhan Berk Başoğlu 2025-11-15 19:33:23 -05:00
parent 2dac32eab0
commit c2e8cfa06d
Signed by: batuhan-basoglu
SSH key fingerprint: SHA256:kEsnuHX+qbwhxSAXPUQ4ox535wFHu/hIRaa53FzxRpo
2 changed files with 5 additions and 7 deletions
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multilayer-perceptron.py
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@ -119,23 +119,23 @@ class MLP:
def plot_graph(self, train_losses, val_accuracies):
if not os.path.exists('results'):
os.makedirs('results')
os.makedirs('results') # creates results director
fig, ax1 = plt.subplots()
fig, ax1 = plt.subplots() # initializes the plot
ax1.set_xlabel('Epochs')
ax1.set_ylabel('Training Loss', color='tab:blue')
ax1.plot(range(1, len(train_losses) + 1), train_losses, color='tab:blue', label='Training Loss')
ax1.tick_params(axis='y', labelcolor='tab:blue')
ax1.tick_params(axis='y', labelcolor='tab:blue') # defines loss subplot
ax2 = ax1.twinx()
ax2.set_ylabel('Validation Accuracy', color='tab:orange')
ax2.plot(range(1, len(val_accuracies) + 1), val_accuracies, color='tab:orange', label='Validation Accuracy')
ax2.tick_params(axis='y', labelcolor='tab:orange')
ax2.tick_params(axis='y', labelcolor='tab:orange') # defines accuracy subplot
plt.title('Training Loss and Validation Accuracy over Epochs')
result_path = 'results/MLP-output.png'
result_path = 'results/MLP-output.png' # defines the file name
fig.savefig(result_path)
print(f"Graph saved to: {result_path}")