diff --git a/machine_learning/classification_models.py b/machine_learning/classification_models.py
index 852a36c..6a2bb1a 100644
--- a/machine_learning/classification_models.py
+++ b/machine_learning/classification_models.py
@@ -60,36 +60,60 @@ class ClassificationModels:
             print("\n************************************\n")
             print("Current model:", model_title, end="\n")
             print("Acc:", model["metrics"][0] / n_clusters)
-            scores_df.append(
-                {
-                    "method": model_title,
-                    "metric": "test_accuracy",
-                    "mean": model["metrics"][0] / n_clusters,
-                }
+            scores_df = pd.concat(
+                [
+                    scores_df,
+                    pd.DataFrame(
+                        {
+                            "method": model_title,
+                            "metric": "test_accuracy",
+                            "mean": model["metrics"][0] / n_clusters,
+                        }
+                    ),
+                ],
+                ignore_index=True,
             )
             print("Precision:", model["metrics"][1] / n_clusters)
-            scores_df.append(
-                {
-                    "method": model_title,
-                    "metric": "test_precision",
-                    "mean": model["metrics"][1] / n_clusters,
-                }
+            scores_df = pd.concat(
+                [
+                    scores_df,
+                    pd.DataFrame(
+                        {
+                            "method": model_title,
+                            "metric": "test_precision",
+                            "mean": model["metrics"][1] / n_clusters,
+                        }
+                    ),
+                ],
+                ignore_index=True,
             )
             print("Recall:", model["metrics"][2] / n_clusters)
-            scores_df.append(
-                {
-                    "method": model_title,
-                    "metric": "test_recall",
-                    "mean": model["metrics"][2] / n_clusters,
-                }
+            scores_df = pd.concat(
+                [
+                    scores_df,
+                    pd.DataFrame(
+                        {
+                            "method": model_title,
+                            "metric": "test_recall",
+                            "mean": model["metrics"][2] / n_clusters,
+                        }
+                    ),
+                ],
+                ignore_index=True,
             )
             print("F1:", model["metrics"][3] / n_clusters)
-            scores_df.append(
-                {
-                    "method": model_title,
-                    "metric": "test_f1",
-                    "mean": model["metrics"][3] / n_clusters,
-                }
+            scores_df = pd.concat(
+                [
+                    scores_df,
+                    pd.DataFrame(
+                        {
+                            "method": model_title,
+                            "metric": "test_f1",
+                            "mean": model["metrics"][3] / n_clusters,
+                        }
+                    ),
+                ],
+                ignore_index=True,
             )
             scores = pd.concat([scores, scores_df])
         return scores