Nonparametric genetic clustering: comparison of validity indices

@article{Bandyopadhyay2001NonparametricGC,
  title={Nonparametric genetic clustering: comparison of validity indices},
  author={Sanghamitra Bandyopadhyay and Ujjwal Maulik},
  journal={IEEE Trans. Syst. Man Cybern. Syst.},
  year={2001},
  volume={31},
  pages={120-125}
}
A variable-string-length genetic algorithm (GA) is used for developing a novel nonparametric clustering technique when the number of clusters is not fixed a-priori. Chromosomes in the same population may now have different lengths since they encode different number of clusters. The crossover operator is redefined to tackle the concept of variable string length. A cluster validity index is used as a measure of the fitness of a chromosome. The performance of several cluster validity indices… 
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References

SHOWING 1-10 OF 17 REFERENCES
Messy Genetic Algorithms: Motivation, Analysis, and First Results
TLDR
The mGA presented herein repeatedly achieves globally optimal results without prior knowledge of good string arrangements, and it does so at the very first generation in which strings are long enough to cover the problem.
Some new indexes of cluster validity
TLDR
This work reviews two clustering algorithms and three indexes of crisp cluster validity and shows that while Dunn's original index has operational flaws, the concept it embodies provides a rich paradigm for validation of partitions that have cloud-like clusters.
An ISODATA clustering procedure for symbolic objects using a distributed genetic algorithm
On finding the number of clusters
Genetic Algorithms in Search Optimization and Machine Learning
TLDR
This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Pattern Recognition Principles
The present work gives an account of basic principles and available techniques for the analysis and design of pattern processing and recognition systems. Areas covered include decision functions,
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
Abstract Two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space. In both cases, the extremizing
Algorithms for Clustering Data
A Cluster Separation Measure
A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster. The
...
...