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 ...

Stanford University’s Machine Learning (XCS229) is a 100% online, instructor-led course offered by the Stanford School of ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...