diff --git a/script5.py b/script5.py
index afabee2..4645837 100644
--- a/script5.py
+++ b/script5.py
@@ -17,9 +17,9 @@ y = data['Rating']
 # Preprocess the data
 # Convert the categorical columns into numerical representations
 mlb = MultiLabelBinarizer()
-X['Generes'] = mlb.fit_transform(X['Generes'])
-X['Plot Kyeword'] = mlb.fit_transform(X['Plot Kyeword'])
-X['Top 5 Casts'] = mlb.fit_transform(X['Top 5 Casts'].astype(str))
+X['Generes'] = mlb.fit_transform(X['Generes']).tolist()
+X['Plot Kyeword'] = mlb.fit_transform(X['Plot Kyeword']).tolist()
+X['Top 5 Casts'] = mlb.fit_transform(X['Top 5 Casts'].astype(str)).tolist()
 
 # Split the data into training and testing sets
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)