vegclust-package(vegclust)
vegclust-package()所属R语言包：vegclust
Functions for fuzzy and hard clustering of vegetation data
模糊和硬聚类植被数据的功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This package contains functions used to perform fuzzy and hard clustering of vegetation data under different models.
这个软件包包含根据车型不同植被数据进行模糊和硬聚类的功能。
Details
详细信息----------Details----------
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This package is intended to be helpful for generating and maintaining classifications of vegetation. There are two main functions: (1) vegclust is used to create a fuzzy classification from an initial data set (a set of releves of community composition); (2) vegclass is used to classify new data (i.e. new releves) into previous classification structures.
这个软件包专门用于产生和维持的植被分类是有帮助的。主要有两个功能：（1）vegclust的使用，以创建一个模糊的分类从最初的数据集（一组群落组成的releves）;（2）vegclass的使用新的数据分类（即新releves）到以前的分类结构。
（作者）----------Author(s)----------
Miquel De C谩ceres, Forest Science Center of Catalonia
Maintainer: Miquel De C谩ceres <miquelcaceres@gmail.com>
参考文献----------References----------
Forgy, E. W. (1965) Cluster analysis of multivariate data: efficiency vs interpretability of classifications. Biometrics 21, 768-769.
MacQueen, J. (1967) Some methods for classification and analysis of multivariate observations. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, eds L. M. Le Cam and J. Neyman, 1, pp. 281-297. Berkeley, CA: University of California Press.
Dav茅, R. N. and R. Krishnapuram (1997) Robust clustering methods: a unified view. IEEE Transactions on Fuzzy Systems 5, 270-293.
Bezdek, J. C. (1981) Pattern recognition with fuzzy objective functions. Plenum Press, New York.
Krishnapuram, R. and J. M. Keller. (1993) A possibilistic approach to clustering. IEEE transactions on fuzzy systems 1, 98-110.
De C谩ceres, M., Font, X, Oliva, F. (2010) The management of numerical vegetation classifications with fuzzy clustering methods. Journal of Vegetation Science 21 (6): 1138-1151.
实例----------Examples----------
# Loads data [数据加载]
data(wetland)
# This equals the chord transformation (see also 'normalize' option in \code{\link{decostand}} from the vegan package)[这等于和弦转换（参见标准化选项\ {\的链接{decostand}}从素食包的代码）]
wetland.chord = as.data.frame(sweep(as.matrix(wetland), 1, sqrt(rowSums(as.matrix(wetland)^2)), "/"))
# Create noise clustering with 3 clusters. Perform 10 starts from random seeds and keep the best solution[创建噪音聚类与3类。进行10次随机种子开始，并保持最佳的解决方案]
vegclust(wetland.chord, mobileCenters=3, m = 1.2, dnoise=0.75, method="NC", nstart=10)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:16:54
