fuzzy k-means algorithm which 模糊k
improved fuzzy k-means algorithm 改进的模糊K
unsupervised fuzzy k-means algorithm 无监督模糊k
fuzzy K means clustering algorithm 模糊K均值聚类算法
fuzzy K-means cluster algorithm 模糊尺均值聚类
Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.
结果模糊K- 均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、 白质和脑脊液。
In cluster analysis, Fuzzy K-Means (FKM) algorithm is one of the most widely used methods. However, FKM algorithm is much more sensitive to the initialization, and easy to fall into local optimum.
在聚类分析中，模糊k均值算法是目前应用最为广泛的方法之一，然而该算法对初始化敏感，容易陷入局部极值点。
For increasing classifiers classification rate, We make use of the fuzzy theories to K-means algorithm again.
基于K -均值算法的模糊分类器具有很好的分类效果，用它可以很准确的对训练样本进行分类。
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