Create application

application.py

@@ -0,0 +1,77 @@
+import gradio as gr
+import dill
+import pandas as pd
+import xgboost as xgb
+import numpy as np
+import pickle
+
+def decode_file(file_path):
+    with open(file_path, 'rb') as file:
+        obj = pickle.load(file)
+    return obj
+
+model = decode_file('model.pkl')
+
+
+def predict(gender, age, hypertension, ever_married, work_type, heart_disease, avg_glucose_level, bmi, smoking_status, Residence_type):
+
+    gender_mapping = {'Male': 1, 'Female': 0}
+    hypertension_mapping = {'Yes': 1, 'No': 0}
+    ever_married_mapping = {'Yes': 1, 'No': 0}
+    work_type_mapping = {'Private': 2, 'Self-employed': 4, 'Govt_job': 3, 'children': 1, 'Never_worked': 0}
+    heart_disease_mapping = {'Yes': 1, 'No': 0}
+    smoking_status_mapping = {'formerly smoked': 3, 'smokes': 1, 'never smoked': 2, 'Unknown': 0}
+    Residence_type_mapping = {'Urban': 1, 'Rural': 0}
+
+    gender = gender_mapping[gender]
+    hypertension = hypertension_mapping[hypertension]
+    ever_married = ever_married_mapping[ever_married]
+    work_type = work_type_mapping[work_type]
+    heart_disease = heart_disease_mapping[heart_disease]
+    smoking_status = smoking_status_mapping[smoking_status]
+    Residence_type = Residence_type_mapping[Residence_type]
+
+    inputs = [gender, age, hypertension, ever_married, work_type, heart_disease, avg_glucose_level, bmi, smoking_status, Residence_type]
+    input_labels = ['gender', 'age', 'hypertension', 'ever_married', 'work_type', 'heart_disease', 'avg_glucose_level', 'bmi', 'smoking_status', 'Residence_type']
+
+
+    input_df = pd.DataFrame([inputs], columns=input_label)
+
+    prediction = model.predict_proba(input_df)[0][1]
+
+
+    result = "The probability to have a stroke{:.2f}%".format(prediction * 100)  # to give a percentage
+    return result
+
+
+
+
+
+
+input_labels = [
+    'gender', 'age', 'hypertension', 'ever_married', 'work_type', 
+    'heart_disease', 'avg_glucose_level', 'bmi', 'smoking_status', 'Residence_type'
+]
+
+#The Interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.components.Radio(choices=['Female', 'Male'], label="Gender"),
+        gr.components.Slider(label="Age"),
+        gr.components.Radio(choices=['Yes', 'No'], label="Hypertension"),
+        gr.components.Radio(choices=['Yes', 'No'], label="Ever Married"),
+        gr.components.Radio(choices=['Private', 'Self-employed', 'Govt_job', 'children', 'Never_worked'], label="Work Type"),
+        gr.components.Radio(choices=['Yes', 'No'], label="Heart Disease"),
+        gr.components.Number(label="Average Glucose Level"),
+        gr.components.Slider(label="BMI"),
+        gr.components.Radio(choices=['formerly smoked', 'never smoked', 'smokes', 'Unknown'], label="Smoking Status"),
+        gr.components.Radio(choices=['Urban', 'Rural'], label="Residence Type")
+    ],
+    outputs='text',
+    title='Stroke Probability Predictor',
+    description='Predicts the probability of having a stroke based on input features.'
+)
+
+
+iface.launch()