Mark A. Hall

JMLR Journal 2010 Journal Article

WEKA-Experiences with a Java Open-Source Project

• Remco R. Bouckaert
• Eibe Frank
• Mark A. Hall
• Geoffrey Holmes
• Bernhard Pfahringer
• Peter Reutemann
• Ian H. Witten

WEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to be important to its success. Rather than focussing on the software's functionality, we review aspects of project management and historical development decisions that likely had an impact on the uptake of the project. [abs] [ pdf ][ bib ] &copy JMLR 2010. ( edit, beta )

UAI Conference 2003 Conference Paper

Locally Weighted Naive Bayes

• Eibe Frank
• Mark A. Hall
• Bernhard Pfahringer

Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by these results, researchers have looked to overcome naive Bayes primary weakness --- attribute independence --- and improve the performance of the algorithm. This paper presents a locally weighted version of naive Bayes that relaxes the independence assumption by learning local models at prediction time. Experimental results show that locally weighted naive Bayes rarely degrades accuracy compared to standard naive Bayes and, in many cases, improves accuracy dramatically. The main advantage of this method compared to other techniques for enhancing naive Bayes is its conceptual and computational simplicity

ICML Conference 2000 Conference Paper

Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning

• Mark A. Hall