The Impact of Cluster Stability on Class Decomposition in Antibody Display Data

Inese Polaka, Arkady Borisov

Abstract


This article focuses on cluster stability evaluation to assess the characteristics of the dataset and the subclasses found in class decomposition. The evaluation is an iterative process, making small changes to the dataset in every step and reapplying the cluster analysis. These small changes (removing one object from the dataset is repeated for 20 iterations in this case) should not have any impact on clusters if they are stable (meaning that other objects that were not removed stay in the same clusters as in the full clustering).


Keywords:
Сlass decomposition; clustering; cluster stability; data mining

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References


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