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| import gradio as gr | |
| import joblib | |
| from tensorflow.keras.models import load_model | |
| relationship_mapping = { | |
| 'Own-child': 3, | |
| 'Husband': 0, | |
| 'Not-in-family': 1, | |
| 'Unmarried': 4, | |
| 'Wife': 5, | |
| 'Other-relative': 2 | |
| } | |
| marital_status_mapping = { | |
| 'Never-married': 4, | |
| 'Married-civ-spouse': 2, | |
| 'Widowed': 6, | |
| 'Divorced': 0, | |
| 'Separated': 5, | |
| 'Married-spouse-absent': 3, | |
| 'Married-AF-spouse': 1 | |
| } | |
| model_dl = load_model('model_dl_importance.h5') | |
| scaler = joblib.load('scaler.pkl') | |
| def predict_income_dl(relationship, fnlwgt, age, marital_status, model): | |
| rel = relationship_mapping.get(relationship, -1) | |
| mar = marital_status_mapping.get(marital_status, -1) | |
| input_data = [[rel, fnlwgt, age, mar]] | |
| input_data = scaler.transform(input_data) | |
| prediction = model_dl.predict(input_data, verbose=0) | |
| prediction = (prediction > 0.5) | |
| if prediction: | |
| return ">50" | |
| else: | |
| return "<50" | |
| demo = gr.Interface( | |
| fn=predict_income_dl, | |
| inputs=[ | |
| gr.Dropdown(choices=list(relationship_mapping.keys()), label="Relationship"), | |
| gr.Text(label="Final Weight"), | |
| gr.Text(label="Age"), | |
| gr.Dropdown(choices=list(marital_status_mapping.keys()), label="Marital Status"), | |
| # input berupa radio button | |
| gr.Radio( | |
| choices=["Random Forest", "Neural Network"], | |
| value="Random Forest", | |
| label="Model", | |
| info="Select model to use" | |
| ) | |
| ], | |
| outputs="text") | |
| # launch aplikasi | |
| demo.launch(share=True) |