该算法通过引入聚类有效性函数，实现了最优特征数目的自动确定。
The optimal feature number is decided automatically by the introduced cluster validity function.
通过三组数据对这个聚类有效性函数的判决功能和鲁棒性进行了对比研究。
Experimental results show the effectiveness and robustness of this cluster validity function by three data sets.
结果当模糊聚类数为5 ~6时，模糊聚类有效性函数最小，图像处理的效果达到最佳水平。
Results: When fuzzy clustering number for 5-6 and fuzzy clustering validity achieved a minimum level of image processing with the best effect.
为解决聚类数未知条件下面状地理实体的聚类问题，文中提出了一种基于聚类有效性函数的聚类方法。
A cluster validity function-based method is proposed for solving the problem of clustering for area geographical entities when the number of cluster is unknown.
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.
在模糊聚类算法的基础上，提出了一个衡量聚类有效性的函数，以确定模糊规则的数目。
A function for measuring clustering validity based on the fuzzy clustering algorithm is defined with which the number of fuzzy rules can be determined.
在模糊聚类算法的基础上，提出了一个衡量聚类有效性的函数，以确定模糊规则的数目。
A function for measuring clustering validity based on the fuzzy clustering algorithm is defined with which the number of fuzzy rules can be determined.
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