So the current question is whether we can confirm the cluster number directly, not using any assumptions.
因此现在的问题是我们能否比较方便地直接确定聚类数，而不需任何假设。
Performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimum cluster number.
利用两个聚类效果评价指标模糊效果指数FPI和归一化分类墒NCE，确定了最适宜的分区数。
The improved fuzzy C-means clustering algorithm has better robustness and makes the cluster results insensitive to the predefined cluster number.
改进后的模糊C-均值聚类算法具有更好的鲁棒性，且放松了隶属度条件，使得最终聚类结果对预先确定的聚类数目不敏感。
The improved fuzzy C-means clustering algorithm has better robustness and makes the cluster results insensitive to the predefined cluster number.
改进后的模糊C-均值聚类算法具有更好的鲁棒性，且放松了隶属度条件，使得最终聚类结果对预先确定的聚类数目不敏感。
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