correctifs

frontend/pages/prediction_classification.py

@@ -3,6 +3,7 @@ from sklearn.linear_model import LogisticRegression
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import accuracy_score
 from sklearn.preprocessing import LabelEncoder
+import pandas as pd
 
 st.header("Prediction: Classification")
 
@@ -53,7 +54,7 @@ if "data" in st.session_state:
                 value = st.number_input(f"Value for {feature}", value=0.0)
                 pred_values.append(value)
         
-        prediction = model.predict([pred_values])
+        prediction = model.predict(pd.DataFrame([pred_values], columns=data_name))
 
         if target_name in label_encoders:
             prediction = label_encoders[target_name].inverse_transform(prediction)

frontend/pages/prediction_regression.py

@@ -1,5 +1,6 @@
 import streamlit as st
 from sklearn.linear_model import LinearRegression
+import pandas as pd
 
 st.header("Prediction: Regression")
 
@@ -21,7 +22,7 @@ if "data" in st.session_state:
         
         st.subheader("Enter values for prediction")
         pred_values = [st.number_input(f"Value for {feature}", value=0.0) for feature in data_name]
-        prediction = model.predict([pred_values])
+        prediction = model.predict(pd.DataFrame([pred_values], columns=data_name))
 
         st.write("Prediction:", prediction[0])
 else: