Traffic classification (TC) is a fundamental task of network management and monitoring operations. Previous works relying on selected packet header fields (e.g. port numbers) or application layer ...

The algorithms examined include decision trees, K-nearest neighbors, random forests, support vector machines, XGBoost, gradient boosting, and bagging. Gradient boosting achieves the highest global ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the gradient boosting regression technique, where the goal is to predict a single numeric value. Compared to ...

The gradient boosting model achieved an 88.2% accuracy in classifying interactome hub genes in samples related to peri-implantitis and periodontitis. Discussion: These identified genes play roles in ...

Computer scientists have written a network flow algorithm that computes almost as fast as is mathematically possible. This algorithm computes the maximum traffic flow with minimum transport costs ...

Thus, in this work, we perform boosting algorithm supervised learning to handle such an unbalanced classification toward PM2.5 concentration levels by observing meteorological patterns in Jakarta ...