lcsekar commited on
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8c8d566
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1 Parent(s): 63e0ec1

Upload folder using huggingface_hub

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  1. app.py +20 -12
app.py CHANGED
@@ -15,19 +15,27 @@ based on user details such as age, occupation, gender, marital status and income
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  Please enter the app details below to get the prediction.
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  """)
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- # # User input
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- # app_category = st.selectbox("App Category", ["FAMILY", "TOOLS", "NEWS AND MAGAZINES", "GAME", "EDUCATION", "OTHERS"])
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- # free_or_paid = st.selectbox("Free or Paid", ["Free", "Paid"])
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- # content_rating = st.selectbox("Content Rating", ["Everyone", "Teen", "Mature 17+", "Adults only 18+"])
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- # screentime_category = st.selectbox("Screen Time Category", ["Low", "Medium", "High"])
 
 
 
 
 
 
 
 
 
 
 
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- # app_size = st.number_input("App Size (MB)", min_value=1.0, max_value=1000.0, value=50.0, step=0.1)
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- # price = st.number_input("Price (USD)", min_value=0.0, max_value=100.0, value=0.0, step=0.1)
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- # installs = st.number_input("Number of Installs", min_value=0, max_value=100000000, value=1000, step=100)
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- # screen_time = st.number_input("Average Screen Time (minutes)", min_value=0, max_value=500, value=30)
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- # active_users = st.number_input("Active Users", min_value=0, max_value=10000000, value=1000, step=100)
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- # short_ads = st.number_input("Short Ads per Hour", min_value=0, max_value=10, value=2)
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- # long_ads = st.number_input("Long Ads per Hour", min_value=0, max_value=10, value=1)
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  # # Assemble input into DataFrame
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  # input_data = pd.DataFrame([{
 
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  Please enter the app details below to get the prediction.
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  """)
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+ # User input
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+ customer_id = st.number_input("Customer ID", min_value=1)
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+ age = st.number_input("Age", min_value=18, max_value=100, value=30)
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+ type_of_contact = st.selectbox("Type of Contact", ["Self Enquiry", "Company Invited"])
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+ city_tier = st.selectbox("City Tier", [1, 2, 3])
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+ occupation = st.selectbox("Occupation", ["Salaried", "Free Lancer", "Small Business", "Large Business"])
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+ gender = st.selectbox("Gender", ["Male", "Female"])
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+ num_person_visiting = st.number_input("Number of Persons Visiting", min_value=1, max_value=20, value=2)
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+ preferred_property_star = st.selectbox("Preferred Property Star", [3, 4, 5])
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+ marital_status = st.selectbox("Marital Status", ["Single", "Divorced", "Married", "Unmarried"])
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+ num_trips = st.number_input("Number of Trips", min_value=0, max_value=50, value=5)
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+ passport = st.selectbox("Passport", ["Yes", "No"])
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+ own_car = st.selectbox("Own Car", ["Yes", "No"])
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+ num_children_visiting = st.number_input("Number of Children Visiting", min_value=0, max_value=10, value=0)
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+ designation = st.selectbox("Designation", ["Executive", "Manager", "Senior Manager", "AVP", "VP"])
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+ monthly_income = st.number_input("Monthly Income (USD)", min_value=1000, max_value=100000, value=5000)
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+ pitch_satisfaction_score = st.selectbox("Pitch Satisfaction Score", [1, 2, 3, 4, 5])
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+ product_pitched = st.selectbox("Product Pitched", ["Super Deluxe", "Deluxe", "Standard", "Basic", "King"])
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+ num_followups = st.number_input("Number of Followups", min_value=0, max_value=20, value=2)
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+ duration_of_pitch = st.number_input("Duration of Pitch (minutes)", min_value=1, max_value=120, value=30)
 
 
 
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  # # Assemble input into DataFrame
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  # input_data = pd.DataFrame([{