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Many clustering algorithms have been proposed from different research disciplines.
Estivill-Castro, V. Why so many clustering algorithms: a position paper.
It is known that many clustering algorithms are posed as optimization problems, where internal cluster validity functions are utilized as the objectives to find the optimal partitions.
Beyond the expected improvement provided by the averaging effect of many clustering algorithms (clustering committee) aiming at the same goal, some interesting experimental results also show that even committees of completely random partitions may lead to a useful consensus.
Many clustering algorithms like KMCA, HCA are hard clustering algorithms.
Many clustering algorithms including KMCA have a dependency on the number of clusters "K".
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Many existing clustering algorithms are available that converge the nodes in a graph with good bonding.
In recent years, this has been a hot topic among researchers and many different clustering algorithms for VANET have been proposed.
Among many possible clustering algorithms, we decide to utilize the PDT tying structures of the triphone states in the baseline HMMs directly to cluster triphone segments, since the tying structure of a phone state indicates partial similarities among triphone segments.
Since then many subspace clustering algorithms have been designed for the understanding of cellular processes [17] and gene regulatory networks [18], assisting in disease diagnosis [19] and thus, better medical treatments.
These modules are widely ignored by many other clustering algorithms which calculate correlations over all samples.
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