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import gradio as gr | |
import pandas as pd | |
import joblib | |
from sklearn.pipeline import Pipeline | |
from sklearn.impute import SimpleImputer | |
from sklearn.compose import ColumnTransformer | |
from sklearn.preprocessing import StandardScaler, OneHotEncoder | |
from sklearn.linear_model import LogisticRegression | |
# Load the saved full pipeline from the file | |
full_pipeline = joblib.load('pipe.pkl') | |
# Define the predict function | |
def predict(gender, SeniorCitizen, Partner, Dependents, Contract, tenure, MonthlyCharges, | |
TotalCharges, PaymentMethod, PhoneService, MultipleLines, InternetService, | |
OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, | |
StreamingMovies, PaperlessBilling): | |
# Create a DataFrame from the input data | |
input_data = pd.DataFrame({ | |
'gender': [gender] if gender else ['Male'], # Replace None with default value | |
'SeniorCitizen': [SeniorCitizen] if SeniorCitizen is not None else [0], # Replace None with default value | |
'Partner': [Partner] if Partner else ['No'], # Replace None with default value | |
'Dependents': [Dependents] if Dependents else ['No'], # Replace None with default value | |
'tenure': [tenure] if tenure else [1], # Replace None with default value | |
'PhoneService': [PhoneService] if PhoneService else ['Yes'], # Replace None with default value | |
'MultipleLines': [MultipleLines] if MultipleLines else ['No'], # Replace None with default value | |
'InternetService': [InternetService] if InternetService else ['DSL'], # Replace None with default value | |
'OnlineSecurity': [OnlineSecurity] if OnlineSecurity else ['No'], # Replace None with default value | |
'OnlineBackup': [OnlineBackup] if OnlineBackup else ['No'], # Replace None with default value | |
'DeviceProtection': [DeviceProtection] if DeviceProtection else ['No'], # Replace None with default value | |
'TechSupport': [TechSupport] if TechSupport else ['No'], # Replace None with default value | |
'StreamingTV': [StreamingTV] if StreamingTV else ['No'], # Replace None with default value | |
'StreamingMovies': [StreamingMovies] if StreamingMovies else ['No'], # Replace None with default value | |
'Contract': [Contract] if Contract else ['Month-to-month'], # Replace None with default value | |
'PaperlessBilling': [PaperlessBilling] if PaperlessBilling else ['No'], # Replace None with default value | |
'PaymentMethod': [PaymentMethod] if PaymentMethod else ['Electronic check'], # Replace None with default value | |
'MonthlyCharges': [MonthlyCharges] if MonthlyCharges else [0.0], # Replace None with default value | |
'TotalCharges': [TotalCharges] if TotalCharges else [0.0] # Replace None with default value | |
}) | |
# Make predictions using the loaded logistic regression model | |
predictions = full_pipeline.predict(input_data) | |
#return predictions[0] | |
if predictions[0] == "Yes": | |
return "Churn" | |
else: | |
return "Not Churn" | |
# Setting Gradio App Interface | |
with gr.Blocks(css=".gradio-container {background-color: grey}") as demo: | |
gr.Markdown("# Teleco Customer Churn Prediction #\n*This App allows the user to predict whether a customer will churn or not by entering values in the given fields. Any field left blank takes the default value.*") | |
# Receiving ALL Input Data here | |
gr.Markdown("**Demographic Data**") | |
with gr.Row(): | |
gender = gr.Dropdown(label="Gender", choices=["Male", "Female"]) | |
SeniorCitizen = gr.Radio(label="Senior Citizen", choices=[1, 0]) | |
Partner = gr.Radio(label="Partner", choices=["Yes", "No"]) | |
Dependents = gr.Radio(label="Dependents", choices=["Yes", "No"]) | |
gr.Markdown("**Service Length and Charges (USD)**") | |
with gr.Row(): | |
Contract = gr.Dropdown(label="Contract", choices=["Month-to-month", "One year", "Two year"]) | |
tenure = gr.Slider(label="Tenure (months)", minimum=1, step=1, interactive=True) | |
MonthlyCharges = gr.Slider(label="Monthly Charges", step=0.05) | |
TotalCharges = gr.Slider(label="Total Charges", step=0.05) | |
# Phone Service Usage part | |
gr.Markdown("**Phone Service Usage**") | |
with gr.Row(): | |
PhoneService = gr.Radio(label="Phone Service", choices=["Yes", "No"]) | |
MultipleLines = gr.Dropdown(label="Multiple Lines", choices=[ | |
"Yes", "No", "No phone service"]) | |
# Internet Service Usage part | |
gr.Markdown("**Internet Service Usage**") | |
with gr.Row(): | |
InternetService = gr.Dropdown(label="Internet Service", choices=["DSL", "Fiber optic", "No"]) | |
OnlineSecurity = gr.Dropdown(label="Online Security", choices=["Yes", "No", "No internet service"]) | |
OnlineBackup = gr.Dropdown(label="Online Backup", choices=["Yes", "No", "No internet service"]) | |
DeviceProtection = gr.Dropdown(label="Device Protection", choices=["Yes", "No", "No internet service"]) | |
TechSupport = gr.Dropdown(label="Tech Support", choices=["Yes", "No", "No internet service"]) | |
StreamingTV = gr.Dropdown(label="TV Streaming", choices=["Yes", "No", "No internet service"]) | |
StreamingMovies = gr.Dropdown(label="Movie Streaming", choices=["Yes", "No", "No internet service"]) | |
# Billing and Payment part | |
gr.Markdown("**Billing and Payment**") | |
with gr.Row(): | |
PaperlessBilling = gr.Radio( | |
label="Paperless Billing", choices=["Yes", "No"]) | |
PaymentMethod = gr.Dropdown(label="Payment Method", choices=["Electronic check", "Mailed check", "Bank transfer (automatic)", "Credit card (automatic)"]) | |
# Output Prediction | |
output = gr.Text(label="Outcome") | |
submit_button = gr.Button("Predict") | |
submit_button.click(fn= predict, | |
outputs= output, | |
inputs=[gender, SeniorCitizen, Partner, Dependents, Contract, tenure, MonthlyCharges, TotalCharges, PaymentMethod, PhoneService, MultipleLines, InternetService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, PaperlessBilling], | |
), | |
# Add the reset and flag buttons | |
def clear(): | |
output.value = "" | |
return None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None | |
clear_btn = gr.Button("Reset", variant="primary") | |
clear_btn.click(fn=clear, inputs=None, outputs=output) | |
demo.launch(inbrowser = True) |