Large databases are routinely being collected in science, business and medicines. A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand the data by discovering useful categories. However, to date research in data mining has not paid attention to the cognitive factors that make learned categories co...

This paper discusses a novel data mining system devised and developed at Birmingham, which attempts to provide a more effective data mining system. It ties in with the workshop goals in a number of different areas. The system tries to allow users to see the big picture and not get caught up in irrelevant detail too early; it uses perception-based approaches to data mining, and it uses interacti...

1 Computer Science Department, University of Wisconsin Parkside, 900 Wood Road, P.O. Box 2000, Kenosha, WI 53141-2000 [mccann at uwp.edu] Abstract Division is the most intellectually challenging of the basic operators of relational algebra. Although its utility is unquestioned, its presentation by many textbooks, and therefore by many instructors, leaves much to be desired. This paper examines ...

Attribute estimation is an important machine learning problem. It is contained in many tasks, e.g., feature subset selection, constructive induction, decision and regression tree building. Relief algorithms are one of the most successful heuristic measures for solving this problem. The quality estimates of the Relief algorithms have commonly been interpreted as the difference of two probabiliti...