IEEE

Integrated Machine Learning Approach to Phishing Detection: Comparing SVM, Random Forest, and XGBoost Models

Abstract: The objective of this research is to create a phishing detection system that is both efficient and effective. This system will be based on sophisticated machine learning models, including ...
IEEE

A random forest-based machine learning algorithm for predicting onion whole sale price

Abstract: The purpose of this study is to estimate and predict onion wholesale price volatility using statistical and machine learning algorithms. Traditional models like ARIMA and GARCH were compared ...

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
Intuit on MSN

6 steps to train an AI model to do whatever you want

A recent study shows that 1 in 5 people use AI every day. From the chatbot helping you budget smarter to the recommendations ...
Scientific Research Publishing

Machine Learning for Financial Risk Management: Modeling Time-Varying Factor Sensitivities Using Factor Variational Autoencoders ()

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
GitHub

Applied-Machine-Learning-Lab/AMAR

This is the code of the paper 'Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation' (Accepted by AAAI 2025).
Frontiers

Investigating the feasibility of machine learning to guide personalized red blood cell (RBC) transfusion: analyzing the heterogeneity of RBC transfusion in septic patients with ...

1 Department of Critical Care Medicine, Jiangdu People’s Hospital Affiliated to Yangzhou University, Yangzhou, China 2 Department of Emergency Medicine, Yangzhou Jiangdu Traditional Chinese Medicine ...