Goodman-Kruskal measure associated clustering for categorical data Online publication date: Sat, 23-Aug-2014
by Wenxue Huang; Yuanyi Pan; Jianhong Wu
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 4, No. 4, 2012
Abstract: Motivated by business interest of return on investment (ROI) in marketing, we develop a conceptual clustering algorithm for categorical data with a response variable based on a variation to Goodman-Kruskal measure. The key to this algorithm is an implicitly cost-effective dissimilarity measure derived from a probabilistic association rule between the response and the explanatory scenarios. Applications to a real dataset FAMEX96 illustrate how useful information can be mined from marketing data using this dissimilarity measure.
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