This paper reviews Machine Learning (ML), and extends and complements previous work
(Kocabas, 1991; Kalkanis and Conroy, 1991). Although this paper focuses on inductive …

Rules–the clearest, most explored and best understood form of knowledge representation–
are particularly important for data mining, as they offer the best tradeoff between human and …

This article reports an empirical investigation of the accuracy of rules that classify examples
on the basis of a single attribute. On most datasets studied, the best of these very simple …

Cândida Ferreira thoroughly describes the basic ideas of gene expression programming
(GEP) and numerous modifications to this powerful new algorithm. This monograph provides …

This paper describes foil, a system that learns Horn clauses from data expressed as
relations. foil is based on ideas that have proved effective in attribute-value learning …

The CN2 algorithm induces an ordered list of classification rules from examples using
entropy as its search heuristic. In this short paper, we describe two improvements to this …

Decision trees are one of the most popular choices for learning and reasoning from feature-
based examples. They have undergone a number of alterations to deal with language and …

Data mining is often referred to by real-time users and software solutions providers as
knowledge discovery in databases (KDD). Good data mining practice for business …

This note introduces a new attribute selection measure for ID3-like inductive algorithms. This
measure is based on a distance between partitions such that the selected attribute in a node …

FOIL is a learning system that constructs Horn clause programs from examples. This paper
summarises the development of FOIL from 1989 up to early 1993 and evaluates its …