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import pickle |
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import pandas as pd |
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import shap |
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from shap.plots._force_matplotlib import draw_additive_plot |
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import gradio as gr |
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import numpy as np |
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import matplotlib.pyplot as plt |
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loaded_model = pickle.load(open("db_xgb.pkl", 'rb')) |
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explainer = shap.Explainer(loaded_model) |
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def main_func(Diabetes, HighBP, HighChol, CholCheck, BMI, Smoker, Stroke, HeartDiseaseorAttack, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, AnyHealthcare, NoDocbcCost, GenHlth, MentHlth, PhysHlth, DiffWalk, Sex, Age, Education, Income): |
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new_row = pd.DataFrame.from_dict({'Diabetes': Diabetes, 'HighBP': HighBP, 'HighChol': HighChol, 'CholCheck': CholCheck, 'BMI': BMI, 'Smoker': Smoker, 'Stroke': Stroke, 'HeartDiseaseorAttack': HeartDiseaseorAttack, 'PhysActivity':PhysActivity, 'Fruits':Fruits, 'Veggies':Veggies, 'HvyAlcoholConsump': HvyAlcoholConsump, 'AnyHealthcare': AnyHealthcare, 'NoDocbcCost': NoDocbcCost, 'GenHlth': GenHlth, 'MentHlth': MentHlth, 'PhysHlth': PhysHlth, 'DiffWalk': DiffWalk, 'Sex': Sex, 'Age': Age, 'Education': Education, 'Income': Income}, |
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orient = 'index').transpose() |
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prob = loaded_model.predict_proba(new_row) |
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shap_values = explainer(new_row) |
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plot = shap.plots.bar(shap_values[0], max_display=6, order=shap.Explanation.abs, show_data='auto', show=False) |
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plt.tight_layout() |
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local_plot = plt.gcf() |
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plt.close() |
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return {"Low Chance": float(prob[0][0]), "High Chance": 1-float(prob[0][0])}, local_plot |
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title = "**Diabetes Predictor & Interpreter** 🪐" |
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description1 = """This app takes info from subjects and predicts their diabetes likelihood. Do not use for medical diagnosis.""" |
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description2 = """ |
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To use the app, click on one of the examples, or adjust the values of the factors, and click on Analyze. 🤞 |
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""" |
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with gr.Blocks(title=title) as demo: |
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gr.Markdown(f"## {title}") |
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gr.Markdown(description1) |
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gr.Markdown("""---""") |
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gr.Markdown(description2) |
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gr.Markdown("""---""") |
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Diabetes = gr.Slider(label="Diabetes Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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HighBP = gr.Slider(label="BP Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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HighChol = gr.Slider(label="Cholesterol Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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CholCheck = gr.Slider(label="CholCheck Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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BMI = gr.Number(label="BMI Score", minimum = 0, maximum = 98, value = 1) |
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Smoker = gr.Slider(label="Smoker Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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Stroke = gr.Slider(label="Stroke Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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HeartDiseaseorAttack = gr.Slider(label="HeartDiseaseorAttack Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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PhysActivity = gr.Slider(label="Physical Activity Score", minimum = 0, maximum = 1, value = 1, step = 1)) |
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Fruits = gr.Slider(label="Fruits Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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Veggies = gr.Slider(label="Veggies Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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HvyAlcoholConsump = gr.Slider(label="Alcohol Consumption Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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AnyHealthcare = gr.Slider(label="AnyHealthcare Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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NoDocbcCost = gr.Slider(label="NoDocbcCost Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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GenHlth = gr.Slider(label="GenHlth Score", minimum = 1, maximum = 5, value = 1, step = 1) |
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PhysHealth = gr.Number(label="PhysHealth Score", minimum = 0, maximum = 30, value=1) |
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MentHlth = gr.Number(label="MentHlth Score", minimum = 0, maximum = 30, value = 1, step = 1) |
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DiffWalk = gr.Number(label="DiffWalk Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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Sex = gr.Slider(label="sex Score", minimum = 0, maximum = 1, value = 1, step = 1) |
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Age = gr.Number(label="age Score", minimum = 1, maximum = 100, value = 1) |
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Education = gr.Slider(label="Education Score", minimum = 1, maximum = 6, value = 1, step = 1) |
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Income = gr.Slider(label="Income Score", minimum = 1, maximum = 8, value = 1, step = 1) |
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submit_btn = gr.Button("Analyze") |
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with gr.Column(visible=True) as output_col: |
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label = gr.Label(label = "Predicted Label") |
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local_plot = gr.Plot(label = 'Shap:') |
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submit_btn.click( |
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main_func, |
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[Diabetes, HighBP, HighChol, CholCheck, BMI, Smoker, Stroke, HeartDiseaseorAttack, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, AnyHealthcare, NoDocbcCost, GenHlth, MentHlth, PhysHlth, DiffWalk, Sex, Age, Education, Income], |
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[label,local_plot], api_name="Diabetes_Predictor" |
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) |
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gr.Markdown("### Click on any of the examples below to see how it works:") |
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gr.Examples([[0,0,1,0,22,0,0,0,1,1,1,0,0,1,3,25,23,1,1,21,5,3], [1,1,1,1,30,1,1,1,0,0,0,1,1,0,2,20,23,0,0,21,3,2]], [Diabetes, HighBP, HighChol, CholCheck, BMI, Smoker, Stroke, HeartDiseaseorAttack, PhysActivity, Fruits, Veggies, HvyAlcoholConsump, AnyHealthcare, NoDocbcCost, GenHlth, MentHlth, PhysHlth, DiffWalk, Sex, Age, Education, Income], [label,local_plot], main_func, cache_examples=True) |
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demo.launch() |
