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What is XGBoost vs Bagging in DNA Classification about?

This document compares the ensemble techniques of XGBoost (boosting) and Random Forest (bagging) for classifying DNA splice junction sequences. Both methods were able to achieve high accuracy for this classification task, with XGBoost achieving 96.24% accuracy and Random Forest achieving 95.11% accuracy when using optimized parameters. The study analyzes the characteristics and performance of each method to provide insight into how they can effectively classify DNA sequence data and assist research in the f

Author

Fatrina

Language

EN