IEEE

A Comparative Analysis of Logistic Regression and Random Forest Algorithm for Cyber Attacks Classification

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 ...
IEEE

Application of Improved Random Forest Method and C4.5 Algorithm as Classifier to Ransomware Detection Based on the Frequency Appearance of API Calls

Abstract: The signature base technique cannot recognize new types of Ransomware without first analyzing it. For that, we need a method to detect Ransomware using machine learning. This study aims to ...
Pagosa Springs SUN

San Juan National Forest to implement prescribed fires

The San Juan National Forest is planning prescribed fire operations as early as March 23, pending all required approvals. We estimate this work to continue through the spring months as weather ...
Frontiers

Forest-EMCBE: an evolutionary ensemble learning algorithm for multiclass diagnosis of bacterial pneumonia using the CBC dataset

Rapid diagnosis of bacterial pneumonia is crucial for clinical diagnosis and treatment, but traditional methods are time-consuming. The wide application of machine learning techniques in medical ...
Scientific Research Publishing

Sitompul, L.R., Nababan, A.A., Manihuruk, M.L., Ponsen, W.A. and Supriyandi, S. (2025) Comparison of XGBoost, Random Forest and Logistic Regression Algorithms in Stroke Disease ...

ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...