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import gradio as gr |
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import joblib |
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import numpy as np |
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model = joblib.load("game_model.joblib") |
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scaler = joblib.load("scaler.joblib") |
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def predict_sales(na, eu, jp, other, year): |
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X = np.array([[na, eu, jp, other, year]]) |
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X_scaled = scaler.transform(X) |
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prediction = model.predict(X_scaled)[0] |
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return float(prediction) |
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interface = gr.Interface( |
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fn=predict_sales, |
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inputs=[ |
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gr.Number(label="NA_Sales"), |
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gr.Number(label="EU_Sales"), |
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gr.Number(label="JP_Sales"), |
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gr.Number(label="Other_Sales"), |
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gr.Number(label="Year") |
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], |
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outputs=gr.Number(label="Predicted Global Sales"), |
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title="Game Sales Predictor", |
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description="Enter game details to predict total worldwide sales." |
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) |
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interface.launch() |
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