We propose a novel context sensitive algorithm for evaluation of ordinal attributes which exploits the information hidden in ordering of attributes’ and class’ values and prov...
Software evolution visualization is a promising technique for assessing the software development process. We study how complex correlations of software evolution attributes can be...
Most of current machine vision systems suffer from a lack of flexibility to account for the high variability of unstructured environments. Here, as the state of the world evolves ...
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, hav...