5 research outputs found
An Exploratory Study of the Inputs for Ensemble Clustering Technique as a Subset Selection Problem
Ensemble and Consensus Clustering address the problem of unifying
multiple clustering results into a single output to best reflect the agreement of
input methods. They can be used to obtain more stable and robust clustering
results in comparison with a single clustering approach. In this study, we propose
a novel subset selection method that looks at controlling the number of clustering
inputs and datasets in an efficient way. The authors propose a number of manual
selection and heuristic search techniques to perform the selection. Our investi‐
gation and experiments demonstrate very promising results. Using these techni‐
ques can ensure better selection methods and datasets for Ensemble and
Consensus Clustering and thus more efficient clustering results
Mathematical Methodologies in Pattern Recognition and Machine LearningContributions from the International Conference on Pattern Recognition Applications and Methods, 2012 /
VIII, 194 p. 58 illus., 40 illus. in color.onlin