Nov. 27, 2005 to Nov. 30, 2005
Richard Butterworth , University of Massachusetts at Boston
Gregory Piatetsky-Shapiro , KDnuggets
Dan A. Simovici , University of Massachusetts at Boston
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2005.106
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the most relevant attributes. The main interest of our technique resides in the improved understanding of the structure of the analyzed data and of the relative importance of the attributes for the selection process.
Richard Butterworth, Gregory Piatetsky-Shapiro, Dan A. Simovici, "On Feature Selection through Clustering", ICDM, 2005, Proceedings. Fifth IEEE International Conference on Data Mining, Proceedings. Fifth IEEE International Conference on Data Mining 2005, pp. 581-584, doi:10.1109/ICDM.2005.106