BIOENGINEER

Kernel-Tuned Machine Learning Pushes Network Intrusion Detection Toward 99% Accuracy on Benchmark Data

A new study reports that Random Forest and Gaussian and Sigmoid kernel Support Vector Machines, combined with systematic ...
BIOENGINEER

New Feature Selection Method Trims Intrusion Detection Models for Industrial Edge Devices

A cluster-preserving feature selection framework cut intrusion detection features from 78 to 27 on the CICIDS2017 benchmark while Random Forest and XGBoost maintained roughly 99.9 percent accuracy.

Part 17: Restricted Boltzmann Machines — Writing probabilities with energy, learning by sampling

From mechanisms with math and Python", Part 17← Previous Part 16: Vanishing Gradients — Why deep networks couldn't ...