Image‐based computer aided diagnosis systems have significant potential for screening
and early detection of malignant melanoma. We review the state of the art in these systems …

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; …

Decision trees have become one of the most powerful and popular approaches in
knowledge discovery and data mining; it is the science of exploring large and complex …

Discrete values have important roles in data mining and knowledge discovery. They are
about intervals of numbers which are more concise to represent and specify, easier to use …

1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms.
1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction …

Having access to massive amounts of data does not necessarily imply that induction
algorithms must use them all. Samples often provide the same accuracy with far less …

Artificial intelligence (AI) is a scientific discipline that aims to create intelligent machines.
Machine learning is a popular and practical AI subfield that aims to automatically improve …

One of the defining challenges for the KDD research community is to enable inductive
learning algorithms to mine very large databases. This paper summarizes, categorizes, and …

This paper provides an analysis of the behavior of separate-and-conquer or covering rule
learning algorithms by visualizing their evaluation metrics and their dynamics in coverage …

In many applications, black-box prediction is not satisfactory, and understanding the data is
of critical importance. Typically, approaches useful for understanding of data involve logical …