Clustering by a genetic algorithm with biased mutation operator

  title={Clustering by a genetic algorithm with biased mutation operator},
  author={Benjamin Auffarth},
  journal={IEEE Congress on Evolutionary Computation},
In this paper we propose a genetic algorithm that partitions data into a given number of clusters. The algorithm can use any cluster validity function as fitness function. Cluster validity is used as a criterion for cross-over operations. The cluster assignment for each point is accompanied by a temperature and points with low confidence are preferentially mutated. We present results applying this genetic algorithm to several UCI machine learning data sets and using several objective cluster… CONTINUE READING

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