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

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