Abstract
Class association rule (CAR), which integrates the techniques of classification and association, is of great interest recently. However, it has two drawbacks: one is that a large part of CARs are spurious; the other one is that some important exception class association rule (ECAR)s are difficult to find. In this paper, we propose a new method to find CAR, remove the spurious class association rule (SCAR)s, and generate ECARs effectively. According to our approach, user can retrieve useful information from useful class association rule (UCAR) and know the influence from different conditions by checking corresponding ECARs. Experimental results demonstrate the effectiveness of our proposed approach.
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© 2000 Springer-Verlag Berlin Heidelberg
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Yu, F., Jin, W. (2000). An Effective Approach to Mining Exception Class Association Rules1 . In: Lu, H., Zhou, A. (eds) Web-Age Information Management. WAIM 2000. Lecture Notes in Computer Science, vol 1846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45151-X_14
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DOI: https://doi.org/10.1007/3-540-45151-X_14
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