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app.py

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+import gradio as gr
+import pandas as pd
+import pickle
+
+# Modeli yükle
+with open('creditcard.pkl', 'rb') as file:
+    model = pickle.load(file)
+
+# Tahmin fonksiyonu
+def predict_fraud(Time, V1, V2, V3, V4, V5, V6, V7, V8, V9, V10, V11, V12, V13, V14, V15, V16, V17, V18, V19, V20, V21, V22, V23, V24, V25, V26, V27, V28, Amount):
+    input_data = pd.DataFrame([[Time, V1, V2, V3, V4, V5, V6, V7, V8, V9, V10, V11, V12, V13, V14, V15, V16, V17, V18, V19, V20, V21, V22, V23, V24, V25, V26, V27, V28, Amount]], 
+                              columns=['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10', 'V11', 'V12', 'V13', 'V14', 'V15', 'V16', 'V17', 'V18', 'V19', 'V20', 'V21', 'V22', 'V23', 'V24', 'V25', 'V26', 'V27', 'V28', 'Amount'])
+    prediction = model.predict(input_data)[0]
+    return 'Fraudulent' if prediction == 1 else 'Not Fraudulent'
+
+# Gradio arayüzü
+inputs = [gr.Number(label=col) for col in ['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10', 'V11', 'V12', 'V13', 'V14', 'V15', 'V16', 'V17', 'V18', 'V19', 'V20', 'V21', 'V22', 'V23', 'V24', 'V25', 'V26', 'V27', 'V28', 'Amount']]
+
+outputs = gr.Textbox(label="Prediction")
+
+gr.Interface(fn=predict_fraud, inputs=inputs, outputs=outputs, title="Credit Card Fraud Detection", description="Enter the transaction details to predict whether it is fraudulent or not.").launch(share=True)

creditcard.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c78f6ab452231e2923e6bcdf994f7cce13edd20e39f97baaa7748948154c0214
+size 180450

requirements.txt

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+pandas==1.5.3
+scikit-learn==1.2.2
+xgboost==1.7.6
+gradio==3.34.0
+numpy==1.24.3