This example illustrates a basic structure of combining a CNN model, a Random Forest model, and an XGBoost model for error compensation in a sequential manner. Further refinement and tuning are essential for optimizing performance based on your specific dataset and use case.
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This example illustrates a basic structure of combining a CNN model, a Random Forest model, and an XGBoost model for error compensation in a sequential manner. Further refinement and tuning are essential for optimizing performance based on your specific dataset and use case.
sujanme25/CNN-RFR-EC-XGB
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This example illustrates a basic structure of combining a CNN model, a Random Forest model, and an XGBoost model for error compensation in a sequential manner. Further refinement and tuning are essential for optimizing performance based on your specific dataset and use case.
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