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Evolving Feature Selection
Found in: IEEE Intelligent Systems
By Huan Liu, Edward R. Dougherty, Jennifer G. Dy, Kari Torkkola, Eugene Tuv, Hanchuan Peng, Chris Ding, Fuhui Long, Michael Berens, Lance Parsons, Zheng Zhao, Lei Yu, George Forman
Issue Date:November 2005
pp. 64-76
Feature selection is a preprocessing technique, commonly used on high-dimensional data, that studies how to select a subset or list of attributes or variables that are used to construct models describing data. Wide data sets, which have a huge number of fe...
Scoring Levels of Categorical Variables with Heterogeneous Data
Found in: IEEE Intelligent Systems
By Eugene Tuv, George C. Runger
Issue Date:March 2004
pp. 14-19
<p>Data modeling in industry is often challenged by the complexity of massive, heterogeneous (mixed-type) data sets. Furthermore, categorical variables can potentially have hundreds (or even thousands) of levels (values). This work explores an effici...