Many KDD systems incorporate an implicit or explicit preference for simpler models, but this
use of “Occam's razor” has been strongly criticized by several authors (eg, Schaffer, 1993; …

Classification rule mining aims to discover a small set of rules in the database that forms an
accurate classifier. Association rule mining finds all the rules existing in the database that …

Summary form only given. Constructing fast, accurate classifiers for large data sets is an
important task in data mining and knowledge discovery. In this research paper, a new …

We present a novel approach to machine learning, called ABML (argumentation based ML).
This approach combines machine learning from examples with concepts from the field of …

Classification rule mining aims to discover a small set of rules in the database that forms an
accurate classifier. Association rule mining finds all the rules existing in the database that …

Occam's razor has been the subject of much controversy. This paper argues that this is partly
because it has been interpreted in two quite different ways, the first of which (simplicity is a …

Explores a promising data mining approach. Despite the small number of examples
available in the authors' application domain (taking into account the large number of …

This paper describes an approach to the detection of events in complex, multi-channel, high
frequency data. The example used is that of detecting the re-siting of a transcutaneous O …

Many existing data mining techniques often produce a large number of rules, which make it
very difficult for manual inspection of the rules to identify those interesting ones. This …

Traditional classification techniques such as decision trees and RIPPER use heuristic
search methods to find a small subset of patterns. In recent years, a promising new …