2010Microelectronics & ComputerRequires access

An Improved Algorithm of Hierarchical Clustering

Mingxin Zhang

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Abstract

In order to achieve clustering well,a modified hierarchical clustering algorithm is proposed based on the strengths and weaknesses of hierarchical clustering(agglomerative) algorithm and neural network ART2 algorithm.Improved algorithm will first use an improved ART2 clustering algorithm to form initial clustering results,and then achieve hierarchical clustering result by agglomerative clustering algorithm based on the results of the previous.It is proved that the proposed algorithm is not only faster than the traditional clustering algorithm,but also the clustering result is better.

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What this paper is about

In order to achieve clustering well,a modified hierarchical clustering algorithm is proposed based on the strengths and weaknesses of hierarchical clustering(agglomerative) algorithm and neural network ART2 algorithm.Improved algorithm will first use an improved ART2 clustering algorithm to form initial clustering results,and then achieve hierarchical clustering result by agglomerative clustering algorithm based on the results of the previous.It is proved that the proposed algorithm is not only faster than the traditional clustering algorithm,but also the clustering result is better.

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Available abstract

In order to achieve clustering well,a modified hierarchical clustering algorithm is proposed based on the strengths and weaknesses of hierarchical clustering(agglomerative) algorithm and neural network ART2 algorithm.Improved algorithm will first use an improved ART2 clustering algorithm to form initial clustering results,and then achieve hierarchical clustering result by agglomerative clustering algorithm based on the results of the previous.It is proved that the proposed algorithm is not only faster than the traditional clustering algorithm,but also the clustering result is better.

Key concepts: Cluster analysis, Computer science, Canopy clustering algorithm, CURE data clustering algorithm, Hierarchical clustering, Correlation clustering, Single-linkage clustering, Hierarchical clustering of networks

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