Missing Clusters Indicate Poor Estimates or Guesses of a Proper Fuzzy Exponent
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Expert Systems with Applications: An International Journal
How Much True Structure Has Been Discovered?
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Discovery of gene regulatory networks in aspergillus fumigatus
KDECB'06 Proceedings of the 1st international conference on Knowledge discovery and emergent complexity in bioinformatics
Clustering Stability: An Overview
Foundations and Trends® in Machine Learning
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We introduce an approach for validating clustering results based on partition stability under a nearestneighbor resampling. The approach is relatively robust, efficient, and avoids conceptual problems of other common validation strategies. Encouraging results compared to those of subsampling-based consensus clustering are presented for simulated data and (tumor) gene expression benchmark data sets. The proposed method is discussed in view of future applications to unsupervised learning from sample data.