Abstract: This study investigates feature selection using L1 and L2 regularization methods associated with logistic regression (LR) by leveraging its coefficient-based feature ranking. This research ...
Abstract: This research aims to compare the performance of Logistic Regression and Random Forest algorithms in classifying cyber-attack types. Using a data set consisting of 494,021 data points with ...