IEEE

A Comparative Analysis of Logistic Regression, Support Vector Machines, and Random Forest for Phishing Website Identification

Abstract: The effectiveness of Logistic Regression (LR), Support Vector Machines (SVM), and Random Forest (RF) in identifying phishing websites is evaluated in this study using a carefully selected ...
GitHub

Project Title: Feature Engineering and Imbalanced Data in Money Laundering Detection: A Comparative Study of ML Algorithms

This project primarily used the small dataset with a high illicit ratio, which contains 5,078,345 financial transactions spanning 10 days.It effectively addresses challenges such as overlap and ...
GitHub

EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

EAGLE (Extrapolation Algorithm for Greater Language-model Efficiency) is a new baseline for fast decoding of Large Language Models (LLMs) with provable performance maintenance. This approach involves ...
IEEE

Evaluating SVM and Soft Voting Ensemble Methods for Classifying Stress Levels Among University Students

Abstract: This study investigates the classification of university students' stress levels using anonymous text posts collected from online platforms where students commonly express their emotions.