IEEE

Tabular Data Classification and Regression: XGBoost or Deep Learning With Retrieval-Augmented Generation

Abstract: Tabular data is the most prevalent form of structured data, necessitating robust models for classification and regression tasks. Traditional models like eXtreme Gradient Boosting (XGBoost) ...
GitHub

TabPFGen: Synthetic Tabular Data Generation with TabPFN

TabPFGen is a Python library for generating high-quality synthetic tabular data using energy-based modeling and stochastic gradient Langevin dynamics (SGLD). It supports both classification and ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
IEEE

An Undersampling Method Based on Spatial Distance and Output Change for Computational Cost Reduction of Regression Models of Engineering Data

Abstract: Excessive computational cost is one of the main reasons limiting the application of regression analysis in engineering data mining. In this article, an undersampling method is proposed to ...