Update code.txt

code.txt

@@ -57,3 +57,35 @@ def main():
 
 if __name__ == "__main__":
     main()
+
+
+import numpy as np
+from sklearn.metrics import confusion_matrix, precision_score, recall_score, f1_score, accuracy_score
+
+# Assuming you have true labels and predicted labels
+y_true = [0, 1, 2, 1, 0, 1, 2, 2, 0]  # Replace with your true labels
+y_pred = [0, 0, 2, 1, 0, 1, 2, 1, 0]  # Replace with your predicted labels
+
+# Calculate the confusion matrix
+conf_matrix = confusion_matrix(y_true, y_pred)
+
+# Print the confusion matrix
+print("Confusion Matrix:")
+print(conf_matrix)
+
+# Calculate precision, recall, f1-score, and accuracy for each label
+precision = precision_score(y_true, y_pred, average=None)
+recall = recall_score(y_true, y_pred, average=None)
+f1 = f1_score(y_true, y_pred, average=None)
+accuracy = accuracy_score(y_true, y_pred)
+
+# Print precision, recall, f1-score for each label
+for i in range(len(precision)):
+    print(f"Label {i}:")
+    print(f"  Precision: {precision[i]:.4f}")
+    print(f"  Recall: {recall[i]:.4f}")
+    print(f"  F1-Score: {f1[i]:.4f}")
+    print()
+
+# Print overall accuracy
+print(f"Overall Accuracy: {accuracy:.4f}")