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app.py

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+import pandas as pd
+import gradio as gr
+import joblib
+
+
+le=joblib.load('le_col.pkl')
+std=joblib.load('std_col.pkl')
+lg=joblib.load('lg.pkl')
+
+le_col=['gender','education','region','loyalty_status','purchase_frequency','product_category']
+std_col=['age','income','purchase_amount','promotion_usage','satisfaction_score']
+
+
+def Prediction_will_purchase_again_Model(a,g,i,e,r,l,p,pp,c,u,s):
+    try:
+        input_data=pd.DataFrame({
+            'age':[a],
+            'gender':[g],
+            'income':[i],
+            'education':[e],
+            'region':[r],
+            'loyalty_status':[l],
+            'purchase_frequency':[p],
+            'purchase_amount':[pp],
+            'product_category':[c],
+            'promotion_usage':[u],
+            'satisfaction_score':[s]
+    
+        })
+        for col in le_col:
+            input_data[col]=le[col].transform(input_data[col])
+        input_data[std_col]=std.transform(input_data[std_col])
+        prediction=lg.predict(input_data)
+        if prediction==1:
+            return 'Yes'
+        else:
+            return 'No'
+    except Exception as e:
+        return str(e)
+gr.Interface(
+    fn=Prediction_will_purchase_again_Model,
+    inputs=[
+        gr.Number(label='age'),
+        gr.Dropdown(['Male','Female'],label='gender'),
+        gr.Number(label='income'),
+        gr.Dropdown(['Bachelor', 'Masters', 'HighSchool', 'College'],label='education'),
+        gr.Dropdown(['East', 'West', 'South', 'North'],label='region'),
+        gr.Dropdown(['Gold', 'Regular', 'Silver'],label='loyalty_status'),
+        gr.Dropdown(['frequent', 'rare', 'occasional'],label='purchase_frequency'),
+        gr.Number(label='purchase_amount'),
+        gr.Dropdown(['Books', 'Clothing', 'Food', 'Electronics', 'Home', 'Beauty','Health'],label='product_category'),
+        gr.Number(label='promotion_usage'),
+        gr.Number(label='satisfaction_score')
+    ],
+    title='Prediction_will_purchase_again_Model',
+    outputs=gr.Textbox(label='Prediction')
+).launch()

le_col.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:09dc4a6f86055870f8653514863adc2de7c0e4fef088d7bbf580cb74c7fb5922
+size 2197

lg.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6c48c5c92de3a83bfe875480244a0d6fc605843eaba7552b7213817aa18fc123
+size 1455

requirements.txt

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+gradio
+pandas
+joblib
+scikit-learn

std_col.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6136f2f691832974e3696e79f05097332801f953b583c3a7eff3122d8738175f
+size 1103