The full text of this article


Reducing dendrogram instability using clustering based on indiscernibility and indiscernibility level
by R.B. Fajriya Hakim; Subanar Seno; Edi Winarko
International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGCRSIS), Vol. 2, No. 2, 2011


Abstract: The notions of indiscernibility and discernibility are the core concept of classical rough sets to cluster similarities and differences of data objects. In this paper, we use a new method of clustering data based on the combination of indiscernibility (quantitative indiscernibility relation) and its indiscernibility level. The indiscernibility level quantify the indiscernibility of pair of objects among other objects in information systems and this level represent the granularity of pair of objects in information system. For comparison to the new method, the following four clustering methods were selected and evaluated on a simulation dataset: average-, complete- and single-linkage agglomerative hierarchical clustering and Ward's method. The result of this paper shows that the four methods of hierarchical clustering yield dendrogram instability that gives different solution under permutation of input order of data object while the new method reduces dendrogram instability.

Online publication date: Wed, 26-Oct-2011


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGCRSIS):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email