| import pickle |
|
|
| import gradio as gr |
| import pandas as pd |
|
|
|
|
| def rf_predict(GDP, Unemployment, Medical_resources, Past_years_life_expectancy_growth_rate): |
| |
| with open('rf.pkl', 'rb') as f: |
| rf = pickle.load(f) |
| |
| X_test = [GDP, Unemployment, Medical_resources, Past_years_life_expectancy_growth_rate] |
| X_test = pd.DataFrame(X_test).T |
| X_test.columns = ['GDP_per_capita', 'Unemployment_rate', 'Medical_resources_per_capita', |
| 'Past_years_life_expectancy_growth_rate'] |
| y_pred = rf.predict(X_test) |
| return y_pred |
|
|
|
|
| |
| |
| gr.Interface( |
| fn=rf_predict, |
| inputs=[ |
| gr.Textbox(label="GDP"), |
| gr.Textbox(label="Unemployment"), |
| gr.Textbox(label="Medical_resources"), |
| gr.Textbox(label="Past_years_life_expectancy_growth_rate"), |
| ], |
| outputs="number", |
| title="Life Expectancy Prediction" |
| ).launch() |
|
|
