A Study on the Construction of Stable Clustering by Minimizing the Order Bias


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 6, No. 6, pp. 1571-1580, Jun. 1999
10.3745/KIPSTE.1999.6.6.1571,   PDF Download:

Abstract

When a hierarchical structure is derived from data set for data mining and machine learning, using a conceptual clustering algorithm one of the unsupervised learning paradigms, it is not unusual to have a different set of outcomes with respect to the order of processing data objects. To overcome this problem, the first classification process is proceeded to construct an initial partition. The partition is expected to imply the possible range in the number of final classes. We apply center sorting to the data objects in the classes of the partition for new data ordering and build a new partition using ITERATE clustering procedure. We developed an algorithm, REIT that leads to the final partition with stable and best partition score. A number of experiments were performed to show the minimization of order bias effects using the algorithm.


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Cite this article
[IEEE Style]
L. G. Sung, "A Study on the Construction of Stable Clustering by Minimizing the Order Bias," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 6, pp. 1571-1580, 1999. DOI: 10.3745/KIPSTE.1999.6.6.1571.

[ACM Style]
Lee Gye Sung. 1999. A Study on the Construction of Stable Clustering by Minimizing the Order Bias. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 6, (1999), 1571-1580. DOI: 10.3745/KIPSTE.1999.6.6.1571.