搜索资源列表
DIBAPI
- fcm用于进行模糊C均值分割，得到的效果还不错-fcm for fuzzy C-means segmentation, the results have been good
sfcm
- 加入邻域信息的空间模糊c均值聚类算法的代码。-Join neighborhood information, spatial fuzzy c-means clustering algorithm code.
Fuzzy-C-means-clustering
- 模糊C均值聚类算法的C++实现代码模糊C均值聚类算法的C++实现代码-Fuzzy C means clustering algorithm C++ implementation code fuzzy C means clustering algorithm C++ implementation code
C-means-clustering-algorithm
- 利用C++实现C均值聚类算法。模糊c均值聚类算法因算法简单收敛速度快且能处理大数据集，解决问题范围广，易于应用计算机实现等特点受到了越来越多人的关注，并应用于各个领域。-C means clustering algorithm in C++
Fuzzy-C
- 模糊C均值聚类算法的步骤还是比较简单的，模糊C均值聚类（FCM），即众所周知的模糊ISODATA，是用隶属度确定每个数据点属于某个聚类的程度的一种聚类算法。-Fuzzy C-means clustering algorithm is relatively simple steps, fuzzy C-means clustering (FCM), known as fuzzy ISODATA, is used to determine the membership of each data poi
C-Means-clustering-code
- 模糊C均值模式识别聚类算法相关的C++源程序代码-Fuzzy C-means clustering algorithm of pattern recognition related to the C source code
fuzzy-c-means-algorithm
- 模式识别中的模糊c均值算法，详细易懂，适合于用于matlab模式识别编程参考-Pattern recognition, fuzzy c-means algorithm, detailed and easy to understand
Fuzzy-c-means-clustering-algorithm-
- k均值算法是模式识别的聚分类问题，采用模糊C均值对数据集data聚为cluster_n类 -k-means algorithm is a pattern recognition poly classification,by using Fuzzy C-Means data sets, data gathered cluster_n class
Genetic-optimization-of-C-clustering
- 运用遗传优化算法优化模糊C均值聚类，通过全局自适应寻优，寻找出更为精确的模糊聚类中心-Using genetic optimization algorithm to optimize the fuzzy C-means clustering, global adaptive optimization to find a more precise fuzzy clustering center
c-means-(FCM)-
- 通过模糊c-均值（FCM）聚类实现图像的分割-Image segmentation by fuzzy c-means (FCM) clustering
fuzzy-c-means
- 模糊C均值聚类算法，在C均值的基础上加入隶属度。-Fuzzy C-means clustering algorithm, on the basis of the C mean join the membership.
c
- 模式识别以3类为例对C均值和模糊C均值算法进行matlab仿真实验。-Pattern recognition in three categories, for example C-Means and fuzzy C-means algorithm matlab simulation experiments.
mohu-c
- 一种基于Matlab的改进的模糊C均值聚类算法,简单，易懂，非常实用-a very good algorithm for Matlab users, you can get a lot from it
Fuzzy-C-means-algorithm
- 模糊C均值聚类算法用于图像分割，可以直接应用-Fuzzy C-means clustering algorithm for image segmentation, can be directly applied
fuzzy-c-means-clustering
- 用于高维数据或者多维图像的模糊C均值聚类算法-Used for army fuzzy c-means clustering high-dimensional data
improved-fuzzy-c-means-clustering
- 该算法引入遗传算法对模糊c均值算法进行改进，并在iris数据集中进行实验验证，得到很高的正确率。-The algorithm genetic algorithm fuzzy c-means algorithm is improved, and focus on experiments in the iris data to obtain a high accuracy.
fuzzy-c
- 模糊C-均值算法容易收敛于局部极小点，为了克服该缺点，将遗传算法应用于模糊C-均值算法(FCM)的优化计算中，由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最优分类结果。-Fuzzy C- means algorithm is easy to converge to a local minimum, in order to overcome this drawback, the genetic algorithm is applied to the fuzzy C- means
常用聚类
- 常用聚类的MATLAB程序，调试均可用。包含k均值聚类、模糊C均值聚类、模糊减法聚类、谱系聚类(Common clustering MATLAB program, debugging are available. Including k-means clustering, fuzzy C-means clustering, fuzzy subtraction clustering, pedigree clustering)
FCM+KFCM模糊C均值聚类分析算法
- FCM+KFCM聚类分析两种方法的比较，有聚类效果图(FCM+KFCM cluster analysis of the two methods of comparison, there is a clustering effect map.)
2b509aabc32f4a3be87b452a94226f45
- 结合模糊C均值聚类算法与水平集方法的图像分割代码，分割效果良好。(The image segmentation code based on fuzzy c-means clustering algorithm and level set method has a good segmentation effect.)