但是，组合的聚类中心数目会多于实际的聚类数目，造成过度分割。

But the number of these combined clusters may be larger than that of the actual clusters, which may result in the over-segmentation.

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同时，算法可以在训练过程中通过有效性函数自适应地确定最佳聚类数目。

Further more, this method can determine the best clustering number using the validity function in training progress.

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对于许多聚类算法，决定合适的聚类数目至关重要，这称为聚类有效性问题。

For many clustering algorithms, it is very important to determine an appropriate number of clusters, which is called cluster validity problem.

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