diff --git a/exploration/ml_pipeline_classification_with_clustering.py b/exploration/ml_pipeline_classification_with_clustering.py
index d4c7f54..f63f110 100644
--- a/exploration/ml_pipeline_classification_with_clustering.py
+++ b/exploration/ml_pipeline_classification_with_clustering.py
@@ -87,7 +87,7 @@ cmodels = cm.get_cmodels()
 # %% jupyter={"source_hidden": true}
 for k in range(N_CLUSTERS):
     model_input_subset = model_input[model_input["cluster"] == k].copy()
-    bins = [-10, -1, 1, 10]  # bins for z-scored targets
+    bins = [-1, 1, 2, 4]  # bins for z-scored targets
     model_input_subset.loc[:, "target"] = pd.cut(
         model_input_subset.loc[:, "target"],
         bins=bins,
@@ -204,3 +204,13 @@ for k in range(N_CLUSTERS):
 # %% jupyter={"source_hidden": true}
 # Get overall results
 scores = cm.get_total_models_scores(n_clusters=N_CLUSTERS)
+
+# %%
+scores.to_csv(
+    "../presentation/results/PANAS_negative_affect_30min_classification_"
+    + CV_METHOD
+    + "_clust_"
+    + str(N_CLUSTERS)
+    + ".csv",
+    index=False,
+)
diff --git a/machine_learning/classification_models.py b/machine_learning/classification_models.py
index 6a2bb1a..1284525 100644
--- a/machine_learning/classification_models.py
+++ b/machine_learning/classification_models.py
@@ -68,7 +68,8 @@ class ClassificationModels:
                             "method": model_title,
                             "metric": "test_accuracy",
                             "mean": model["metrics"][0] / n_clusters,
-                        }
+                        },
+                        index=[0],
                     ),
                 ],
                 ignore_index=True,
@@ -82,7 +83,8 @@ class ClassificationModels:
                             "method": model_title,
                             "metric": "test_precision",
                             "mean": model["metrics"][1] / n_clusters,
-                        }
+                        },
+                        index=[0],
                     ),
                 ],
                 ignore_index=True,
@@ -96,7 +98,8 @@ class ClassificationModels:
                             "method": model_title,
                             "metric": "test_recall",
                             "mean": model["metrics"][2] / n_clusters,
-                        }
+                        },
+                        index=[0],
                     ),
                 ],
                 ignore_index=True,
@@ -110,7 +113,8 @@ class ClassificationModels:
                             "method": model_title,
                             "metric": "test_f1",
                             "mean": model["metrics"][3] / n_clusters,
-                        }
+                        },
+                        index=[0],
                     ),
                 ],
                 ignore_index=True,