The identification of network attacks which target information and communication systems
has been a focus of the research community for years. Network intrusion detection is a …

Medicine will experience many changes in the coming years because the so-called
“medicine of the future” will be increasingly proactive, featuring four basic elements …

This paper offers a comprehensive approach to feature selection in the scope of
classification problems, explaining the foundations, real application problems and the …

Witten and Frank's textbook was one of two books that 1 used for a data mining class in the
Fall of 2001. The book covers all major methods of data mining that produce a knowledge …

Data Mining Page 1 Data Mining Practical Machine Learning Tools and Techniques Third
Edition Ian H. Witten Eibe Frank Mark A. Hall ELSEVIER AMSTERDAM • BOSTON • …

With increasing Internet connectivity and traffic volume, recent intrusion incidents have
reemphasized the importance of network intrusion detection systems for combating …

In this work, a new method consisting of a combination of discretizers, filters and classifiers
is presented. Its aim is to improve the performance results of classifiers but using a …

Quantitative attributes are usually discretized in Naive-Bayes learning. We establish simple
conditions under which discretization is equivalent to use of the true probability density …

Discretization is a popular approach to handling numeric attributes in machine learning. We
argue that the requirements for effective discretization differ between naive-Bayes learning …

Abstract Success Likelihood Index Model (SLIM) is one of the widely-used deterministic
techniques in human reliability assessment especially when data is insufficient. However …