Description: FCMDEMO displays a GUI window to let you try out various parameters
in fuzzy c-means clustering for 2-D data. You can choose the data set
and clustering number from the GUI buttons at right, and then click
\"Start\" to start the fuzzy clustering process.-FCMDEMO GUI displays a window to let you try out various parameters in fuzzy c-means cluste ring for 2-D data. You can choose the data set and clustering number from the GUI buttons at right , and then click "Start" to start the fuzzy clus tering process. Platform: |
Size: 5714 |
Author:dynasty |
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Description: 模糊核聚类及几篇文章，用于数据和图像的模糊聚类分割，效果还行-nuclear fuzzy clustering and articles for data and image segmentation fuzzy clustering, the results were OK Platform: |
Size: 1381338 |
Author:张莉 |
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Description: FCMDEMO displays a GUI window to let you try out various parameters
in fuzzy c-means clustering for 2-D data. You can choose the data set
and clustering number from the GUI buttons at right, and then click
"Start" to start the fuzzy clustering process.-FCMDEMO GUI displays a window to let you try out various parameters in fuzzy c-means cluste ring for 2-D data. You can choose the data set and clustering number from the GUI buttons at right , and then click "Start" to start the fuzzy clus tering process. Platform: |
Size: 5120 |
Author: |
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Description: 模糊核聚类及几篇文章，用于数据和图像的模糊聚类分割，效果还行-nuclear fuzzy clustering and articles for data and image segmentation fuzzy clustering, the results were OK Platform: |
Size: 1381376 |
Author:张莉 |
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Description: 首先对原始数据 归一化
然后进行PCA分析
采用PCs作为特征，
进行模糊聚类分析 fuzzy c-means method-First normalized the raw data and then proceed to PCA analysis using PCs as features, fuzzy clustering analysis for fuzzy c-means method Platform: |
Size: 1024 |
Author:王一 |
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Description: FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divided into clusters with the greatest similarity between the object, and different similarity between the smallest cluster. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for data delineation is rigid, while the FCM is a soft fuzzy partition. Platform: |
Size: 368640 |
Author:Alpha |
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Description: FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divided into clusters with the greatest similarity between the object, and different similarity between the smallest cluster. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for data delineation is rigid, while the FCM is a soft fuzzy partition. FCM in the introduction prior to the specific algorithm we first introduce some basic knowledge of fuzzy sets. Platform: |
Size: 1713152 |
Author:zhourl |
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Description: 模糊Fcm代码，在matlab下开发，用c划分聚类进行数据分析-Fuzzy FCm code, developed in matlab with c divided into clustering for data analysis Platform: |
Size: 82944 |
Author:sunana |
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Description: 协同模糊聚类建模通过特征选择和协同模糊聚类的模糊建模方法构建T-S模型，并用此模型对数据进行测试。-Collaborative fuzzy clustering modeling and collaboration through the feature selection fuzzy clustering TS fuzzy modeling method to build models and use this model of data for testing. Platform: |
Size: 3072 |
Author:zhangwenming |
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Description:
使用matlab实现的各种聚类算法,其中包括具体例子进行详细说明。-The purpose of the development of this toolbox was to compile a continuously extensible, standard tool, which is useful for any MATLAB user for one s aim. In Chapter 1 of the downloadable related documentation one can find a theoretical introduction containing the theory of the algorithms, the definition of the validity measures and the tools of visualization, which help to understand the programmed MATLAB files.
Chapter 2 deals with the exposition of the
files and the description of the particular algorithms, and they are illustrated with simple examples, while in Chapter 3 the whole
Toolbox is tested on real data sets during the solution of three clustering problems: comparison and selection of algorithms estimating the optimal number of clusters and examining
multidimensional data sets.
About the Toolbox
The Fuzzy Clustering and Data Analysis Toolbox is a collection of MATLAB functions. The toolbox provides five categories of functions:
- Cluste Platform: |
Size: 2143232 |
Author:JinJun |
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Description: kfcm，为模糊核聚类算法，用于将低维的数据映射到高维进行分类，是较先进的算法-kfcm, the fuzzy kernel clustering algorithm for low-dimensional data is mapped to high-dimensional classification, is a more advanced algorithms Platform: |
Size: 1380352 |
Author:wang |
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Description: 基于VC的各种聚类和分类算法程序。
手写数字或者打开已有的手写数字图像后，在右视图空白处，单击鼠标左键，激活右视图，选择菜单中的各种分类算法，可以对手写数字进行分类。有模板匹配分类器、Bayes分类器、线性函数分类法、非线性分类法、神经网络分类器。
在左视图上单击鼠标左键，可获得3种数据源：标准数字聚类、手画图形聚类、位图文件分析聚类。可以进行特征提取、模糊聚类和遗传算法。-VC-based clustering and classification algorithm for a variety of procedures. Handwritten numbers or open an existing handwritten digital images, the empty space in the right view, click the left mouse button to activate the right view, select the menu, the various classification algorithms can be handwritten digits classification. There template matching classifier, Bayes classifier, a linear function of classification, non-linear classification, neural network classifier. In the left view, click the left mouse button, access to three kinds of data sources: a standard digital cluster, hand-painted graphics clustering, clustering analysis of bitmap file. Can feature extraction, fuzzy clustering and genetic algorithm. Platform: |
Size: 3179520 |
Author:ft5272633 |
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Description: 图像特征提取的总结，用MATLAB模糊聚类算法进行图像分割，阀值分割及特征提取的资料和作业。-Summary of the image feature extraction, fuzzy clustering algorithm using MATLAB for image segmentation, threshold segmentation and feature extraction of data and operations. Platform: |
Size: 490496 |
Author:abcd0609 |
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Description: Fuzzy clustering is a class of algorithms for cluster analysis in which the allocation of data points to clusters is not "hard" (all-or-nothing) but "fuzzy" in the same sense as fuzzy logic. Platform: |
Size: 5120 |
Author:bwindhya |
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Description: This paper describes the application of an identification algorithm clustering type Gustafson-Kessel nonlinear
dynamical system. From input-output data the algorithm generates fuzzy models of Takagi-Sugeno. This type of modeling is applied
to a non-linear numerical model. The non-linear input / output model of the system is decomposed in several described by
membership functions and fuzzy rule-based local linear systems. The results are presented and prospects for future work. Platform: |
Size: 152576 |
Author:orques
|
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Search - fuzzy clustering for data