NOCEA: A rule-based evolutionary algorithm for efficient and effective clustering of massive high-dimensional databases

@article{Sarafis2007NOCEAAR,
title={NOCEA: A rule-based evolutionary algorithm for efficient and effective clustering of massive high-dimensional databases},
author={Ioannis A. Sarafis and Philip W. Trinder and Ali M. S. Zalzala},
journal={Appl. Soft Comput.},
year={2007},
volume={7},
pages={668-710}
}

Clustering is a descriptive data mining task aiming to group the data into homogeneous groups. This paper presents a novel evolutionary algorithm (NOCEA) that efficiently and effectively clusters massive numerical databases. NOCEA evolves individuals of variable-length consisting of disjoint and axis-aligned hyper-rectangular rules with homogeneous data distribution. The antecedent part of the rules includes an interval-like condition for each dimension. A novel quantisation algorithm imposes a… CONTINUE READING