Ke Wang, Senqiang Zhou, Chee Ada Fu, Jeffrey Xu Yu  Home/Search
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Abstract: We study the problem of mining changes of classification characteristics as the data changes. Available are an old classifier, representing previous knowledge about classification characteristics, and a new data. We want to find the changes of classification characteristics in the new data. An example of such changes is "members with a large family no longer shop frequently, but they used to". Finding this kind of changes holds the key for the organization to adopt to the changed environment... (Update)
Active bibliography (related documents): More All
1.6: Mining Changes of Classification by Correspondence Tracing - Wang, Zhou, Fu, Yu (Correct)
0.3: Discovering the Set of Fundamental Rule Changes - Liu, Hsu, Ma (2001) (Correct)
0.2: Belief-Evidence Fusion in a Hybrid Intelligent System - Marcos, Azcarraga (Correct)
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0.2: Growing Decision Trees On Support-Less Association Rules - Wang, Zhou, He (2000) (Correct)
0.2: Building Hierarchical Classifiers Using Class Proximity - Wang, Zhou, Liew (1999) (Correct)
0.2: Profit Mining: From Patterns to Actions - Wang, Zhou, Hah (2002) (Correct)
BibTeX entry: (Update)
@misc{ wang-mining,
author = "Ke Wang and Senqiang Zhou and Chee Ada Fu and Jeffrey Xu Yu",
title = "Mining Changes of Classification by Correspondence Tracing",
url = "citeseer.ist.psu.edu/720385.html" }
Citations (may not include all citations):2177 programs for machine learning (context) - Quinlan - 1993
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5 Discovering the set of fundamental rule changes - Liu, Hsu et al. - 2001
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4 Growing decision trees on association rules (context) - Wang, Zhou et al. - 2000
3 Generating classification rules according to user's existing.. (context) - Chen, Liu - 2001
http://kdd.ics.uci.edu/databases/ipums/ipums.html
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