Biclustering based on association analysis
Biclustering based on association analysis
Date
2013-03-27
Authors
Βουτσινάς, Βασίλης
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Clustering has been applied in a wide variety of disciplines and has also been utilized in many scientific areas. Usually, clustering algorithms construct either clusters of rows or clusters of columns of the input data matrix. Biclustering is a methodology where biclusters are formed by both a subset of rows and a subset of columns, such that objects represented by the first are the most similar to each other when compared over the latter. In this paper, we introduce a new biclustering technique, based on association rule mining, which can support different well-known biclustering models proposed in the literature. Experimental tests demonstrate the accuracy and efficiency of the proposed technique with respect to well known related ones.
Description
Keywords
Biclustering, Clustering, Association rule mining, Data mining, High dimensionality