2012 | OriginalPaper | Buchkapitel
A Novel Hierarchical Clustering Scheme Based on Q-Criterion
verfasst von : Li Jianfu, He Huaiqing
Erschienen in: Software Engineering and Knowledge Engineering: Theory and Practice
Verlag: Springer Berlin Heidelberg
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The most important step in hierarchical clustering is to find a pair of clusters with the highest degree of similarity to merge. A widely used evolutionary tree reconstruction algorithm in computational biology, Neighbor joining, defined a similarity metrics based on Q-criterion. A great deal of empirical testing and theoretical studies have showed that the Q-criterion is linear in distances, permutation equivariant, consistent. Motivated by Neighbor joining, this paper proposes a Q-criterion based hierarchical clustering algorithm, named HACNJ. The main contribution of HACNJ is to firstly introduce the Q-criterion to clustering. The final experiment on Iris dataset verifies that HACNJ is effective.