Delete app,py

app,py

@@ -1,63 +0,0 @@
-import pandas as pd
-import pickle
-from sklearn.preprocessing import LabelEncoder
-import streamlit as st
-
-# Load the trained model from data.pkl
-def load_model():
-  with open('data.pkl', 'rb') as file:
-    model = pickle.load(file)
-  return model
-
-# Define the prediction function using the loaded model
-def predict_user_profile(inputs):
-  # Preprocess the input data
-  lang_encoder = LabelEncoder()
-  lang_code = lang_encoder.fit_transform([inputs['Language']])[0]
-
-  # Create a DataFrame from the user input dictionary
-  df = pd.DataFrame.from_dict([inputs])
-
-  # Select the relevant feature columns used during model training
-  feature_columns_to_use = ['statuses_count', 'followers_count', 'friends_count',
-                            'favourites_count', 'listed_count', 'lang_code']
-  df_features = df[feature_columns_to_use]
-
-  # Load the pre-trained model
-  model = load_model()
-
-  # Make predictions using the loaded model
-  prediction = model.predict(df_features)
-
-  # Return the predicted class label (0 for fake, 1 for genuine)
-  return "Genuine" if prediction[0] == 1 else "Fake"
-
-# Create the Streamlit app
-st.title('User Profile Classifier')
-st.write('Predict whether a user profile is genuine or fake.')
-
-# Create input fields for user data
-statuses_count = st.number_input("Statuses Count", min_value=0)
-followers_count = st.number_input("Followers Count", min_value=0)
-friends_count = st.number_input("Friends Count", min_value=0)
-favourites_count = st.number_input("Favourites Count", min_value=0)
-listed_count = st.number_input("Listed Count", min_value=0)
-name = st.text_input("Name")
-language = st.text_input("Language")
-
-# Create a dictionary to store user inputs
-user_input = {
-  "statuses_count": statuses_count,
-  "followers_count": followers_count,
-  "friends_count": friends_count,
-  "favourites_count": favourites_count,
-  "listed_count": listed_count,
-  "name": name,
-  "Language": language
-}
-
-
-# Predict if the user clicks the button
-if st.button("Predict"):
-  prediction = predict_user_profile(user_input)
-  st.write(f"Prediction: {prediction}")