Gradient based fuzzy c-means (GBFCM) algorithm
Gradient based fuzzy c-means (GBFCM) algorithm
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基于梯度的模糊 C 均值 (GBFCM) 算法
DOI：
10.1109/icnn.1994.374399
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发表时间：
1994
期刊：
影响因子：
--
通讯作者：
I. Dagher
中科院分区：
文献类型：
--
作者：
Dong C. Park;I. Dagher
提出了一种基于模糊c均值算法（FCM）和梯度下降法的聚类算法。在FCM中，目标函数的最小化过程是通过迭代方式交替求解两个方程来进行的。每次迭代都需要一次性使用所有数据。在我们提出的方法中，一次一个数据被提交给网络，并使用梯度下降法进行最小化。实验结果表明，与FCM算法相比，该算法在收敛速度和稳定性方面具有很强的竞争力。<<ETX>>
In this paper, a clustering algorithm based on the fuzzy c-means algorithm (FCM) and the gradient descent method is presented. In the FCM, the minimization process of the objective function is proceeded by solving two equations alternatively in an iterative fashion. Each iteration requires the use of all the data at once. In our proposed approach one datum at a time is presented to the network, and the minimization is proceeded using the gradient descent method. Compared to FCM, the experimental results show that our algorithm is very competitive in terms of speed and stability of convergence for large number of data.<<ETX>>