A Threshold Free Clustering Algorithm for Robust Unsupervised Classification

@article{Temel2007ATF,
  title={A Threshold Free Clustering Algorithm for Robust Unsupervised Classification},
  author={Turgay Temel and Nizamettin Aydin},
  journal={2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security (BLISS 2007)},
  year={2007},
  pages={119-122}
}
A new information-theoretic, unsupervised, subtractive clustering algorithm is proposed. The algorithm eliminates threshold constraint to detect possible cluster members. Cluster centers are formed with minimum entropy. Instead of using a fixed- threshold, a decision region is formed with the use of maximum mutual information. Cluster members are chosen… CONTINUE READING