add .pkl file for model and predictions code
Browse files- app.py +28 -2
- tuned_blend_specific_model_19112021.pkl +0 -0
app.py
CHANGED
@@ -3,10 +3,36 @@
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import gradio as gr
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def predict_amputation(age, gender, race, diabetes_type):
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return "ALLAH"
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title = "DIabetes-related Amputation Risk Calculator (DIARC)"
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import gradio as gr
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from pycaret.classification import load_model, predict_model
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# load the trained model for predictions
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model = load_model("tuned_blend_specific_model_19112021")
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# define the function to call
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def predict(model, input_df):
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predictions_df = predict_model(estimator=model, data=input_df)
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predictions = predictions_df["Amputation"][0]
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#input_dict = {"AGE": age, "GENDER_F": gender, "RACE_Asian": ,"RACE_Black": , "RACE_Coloured":, "RACE_Other":, "RACE_White":, "DIABETES_CLASS_Type 1 diabetes":}
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input_dict = {"AGE": 70.0, "GENDER_F": 0.0, "RACE_Asian": 1.0, "RACE_Black": , "RACE_Coloured": 0.0, "RACE_Other": 0.0, "RACE_White": 0.0, "DIABETES_CLASS_Type 1 diabetes":0.0}
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input_df = pd.DataFrame([input_dict])
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# the parameters in this function, actually gets the inputs for the prediction
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def predict_amputation(age, gender, race, diabetes_type):
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return "ALLAH"+predict(model=model, input_df=input_df) # calls the predict function when the 'submit' button is clicked
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title = "DIabetes-related Amputation Risk Calculator (DIARC)"
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tuned_blend_specific_model_19112021.pkl
ADDED
Binary file (4.88 MB). View file
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