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| import pickle | |
| import pandas as pd | |
| import shap | |
| from shap.plots._force_matplotlib import draw_additive_plot | |
| import gradio as gr | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # load the model from disk | |
| loaded_model = pickle.load(open("coupon_xgb.pkl", 'rb')) | |
| # Setup SHAP | |
| explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS. | |
| # Create the main function for server | |
| def main_func(destination,passanger,weather,time,expiration,gender,age,maritalStatus,education,occupation,income,Bar,CoffeeHouse,CarryAway,RestaurantLessThan20,Restaurant20To50,coupon,has_children,toCoupon_GEQ5min,toCoupon_GEQ15min,toCoupon_GEQ25min,direction_same,direction_opp,temperature): | |
| new_row = pd.DataFrame.from_dict({'destination':destination,'passanger':passanger, | |
| 'weather':weather,'time':time,'expiration':expiration, | |
| 'gender':gender,'age':age,'maritalStatus':maritalStatus, | |
| 'education':education,'occupation':occupation,'income':income, | |
| 'Bar':Bar,'CoffeeHouse':CoffeeHouse,'CarryAway':CarryAway, | |
| 'RestaurantLessThan20':RestaurantLessThan20,'Restaurant20To50':Restaurant20To50,'coupon':coupon, | |
| 'has_children':has_children,'toCoupon_GEQ5min':toCoupon_GEQ5min,'toCoupon_GEQ15min':toCoupon_GEQ15min, | |
| 'toCoupon_GEQ25min':toCoupon_GEQ25min,'direction_same':direction_same,'direction_opp':direction_opp, | |
| 'temperature':temperature}, orient = 'index').transpose() | |
| prob = loaded_model.predict_proba(new_row) | |
| shap_values = explainer(new_row) | |
| # plot = shap.force_plot(shap_values[0], matplotlib=True, figsize=(30,30), show=False) | |
| # plot = shap.plots.waterfall(shap_values[0], max_display=6, show=False) | |
| plot = shap.plots.bar(shap_values[0], max_display=24, order=shap.Explanation.abs, show_data='auto', show=False) | |
| plt.tight_layout() | |
| local_plot = plt.gcf() | |
| plt.rcParams['figure.figsize'] = 6,4 | |
| plt.close() | |
| return {"Leave": float(prob[0][0]), "Stay": 1-float(prob[0][0])}, local_plot | |
| # Create the UI | |
| title = "**Employee Turnover Predictor & Interpreter** 🪐" | |
| description1 = """ | |
| This app takes six inputs about employees' satisfaction with different aspects of their work (such as work-life balance, ...) and predicts whether the employee intends to stay with the employer or leave. There are two outputs from the app: 1- the predicted probability of stay or leave, 2- Shapley's force-plot which visualizes the extent to which each factor impacts the stay/ leave prediction. | |
| """ | |
| description2 = """ | |
| To use the app, click on one of the examples, or adjust the values of the six employee satisfaction factors, and click on Analyze. ✨ | |
| """ | |
| with gr.Blocks(title=title) as demo: | |
| gr.Markdown(f"## {title}") | |
| # gr.Markdown("""""") | |
| gr.Markdown(description1) | |
| gr.Markdown("""---""") | |
| gr.Markdown(description2) | |
| gr.Markdown("""---""") | |
| with gr.Row(): | |
| with gr.Column(): | |
| destination = gr.Slider(label="destination Score", minimum=1, maximum=5, value=4, step=.1) | |
| passanger = gr.Slider(label="passanger Score", minimum=1, maximum=5, value=4, step=.1) | |
| weather = gr.Slider(label="weather Score", minimum=1, maximum=5, value=4, step=.1) | |
| time = gr.Slider(label="time Score", minimum=1, maximum=5, value=4, step=.1) | |
| expiration = gr.Slider(label="expiration Score", minimum=1, maximum=5, value=4, step=.1) | |
| gender = gr.Slider(label="gender Score", minimum=1, maximum=5, value=4, step=.1) | |
| age = gr.Slider(label="age Score", minimum=1, maximum=5, value=4, step=.1) | |
| maritalStatus = gr.Slider(label="maritalStatus Score", minimum=1, maximum=5, value=4, step=.1) | |
| education = gr.Slider(label="education Score", minimum=1, maximum=5, value=4, step=.1) | |
| occupation = gr.Slider(label="occupation Score", minimum=1, maximum=5, value=4, step=.1) | |
| income = gr.Slider(label="income Score", minimum=1, maximum=5, value=4, step=.1) | |
| Bar = gr.Slider(label="Bar Score", minimum=1, maximum=5, value=4, step=.1) | |
| CoffeeHouse = gr.Slider(label="CoffeeHouse Score", minimum=1, maximum=5, value=4, step=.1) | |
| CarryAway = gr.Slider(label="CarryAway Score", minimum=1, maximum=5, value=4, step=.1) | |
| RestaurantLessThan20 = gr.Slider(label="RestaurantLessThan20 Score", minimum=1, maximum=5, value=4, step=.1) | |
| Restaurant20To50 = gr.Slider(label="Restaurant20To50 Score", minimum=1, maximum=5, value=4, step=.1) | |
| coupon = gr.Slider(label="Coupon Score", minimum=1, maximum=5, value=4, step=.1) | |
| has_children = gr.Slider(label="Has_children Score", minimum=1, maximum=5, value=4, step=.1) | |
| toCoupon_GEQ5min = gr.Slider(label="toCoupon_GEQ5min Score", minimum=1, maximum=5, value=4, step=.1) | |
| toCoupon_GEQ15min = gr.Slider(label="toCoupon_GEQ15min Score", minimum=1, maximum=5, value=4, step=.1) | |
| toCoupon_GEQ25min = gr.Slider(label="toCoupon_GEQ25min Score", minimum=1, maximum=5, value=4, step=.1) | |
| direction_same = gr.Slider(label="direction_same Score", minimum=1, maximum=5, value=4, step=.1) | |
| direction_opp = gr.Slider(label="direction_opp Score", minimum=1, maximum=5, value=4, step=.1) | |
| temperature = gr.Slider(label="temperature Score", minimum=1, maximum=5, value=4, step=.1) | |
| submit_btn = gr.Button("Analyze") | |
| with gr.Column(visible=True,scale=1, min_width=600) as output_col: | |
| label = gr.Label(label = "Predicted Label") | |
| local_plot = gr.Plot(label = 'Shap:') | |
| submit_btn.click( | |
| main_func, | |
| [destination,passanger,weather,time,expiration,gender,age,maritalStatus,education,occupation,income,Bar,CoffeeHouse,CarryAway,RestaurantLessThan20,Restaurant20To50], | |
| [label,local_plot], api_name="Employee_Turnover" | |
| ) | |
| gr.Markdown("### Click on any of the examples below to see how it works:") | |
| gr.Examples([[4,4,4,4,5,5,4,4,4,4,5,5,4,4,4,4], [5,4,5,4,4,4,5,4,5,4,4,4,5,4,5,4]], | |
| [destination,passanger,weather,time,expiration,gender,age,maritalStatus,education,occupation,income,Bar,CoffeeHouse,CarryAway,RestaurantLessThan20,Restaurant20To50], | |
| [label,local_plot], main_func, cache_examples=True) | |
| demo.launch() |