vegclass(vegclust)
vegclass()所属R语言包：vegclust
Classifies vegetation communities
植被群落分类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Classifies vegetation communities into a previous fuzzy or hard classification.
分类到先前的模糊或硬分类的植被群落。
用法----------Usage----------
vegclass(y, x)
参数----------Arguments----------
参数：y
An object of class vegclust that represents a previous knowledge.
一个对象的类vegclust的，代表了以前的知识。
参数：x
Community data to be classified, in form of a site by species matrix (if the vegclust object is in raw mode) or a data frame containing the distances between the new sites in rows and the old sites in columns (if the vegclust object is in distance mode).
社区数据进行分类，物种矩阵（，如果vegclust对象是在raw模式）或新的站点以行和列中的旧网站之间的距离的数据框包含一个站点的形式（如果vegclust对象是在distance模式）。
Details
详细信息----------Details----------
This function uses the classification model specified in y to classify the communities (rows) in x. When vegclust is in raw mode, the function calls first to conformveg in order to cope with different sets of species. See the help of as.vegclust to see an example of vegclass with distance matrices.
此功能使用指定的y分类社区（行）x的分类模型。当vegclust是在raw模式，函数调用的第一个conformveg，以应付不同的物种。请参阅帮助as.vegclust看vegclass的距离矩阵的一个例子。
值----------Value----------
Returns an object of type vegclass with the following items: <table summary="R valueblock"> <tr valign="top"><td>method</td> <td> The clustering model used in y</td></tr> <tr valign="top"><td>m</td> <td> The fuzziness exponent in y</td></tr> <tr valign="top"><td>dnoise</td> <td> The distance to the noise cluster used for noise clustering (NC). This is set to NULL for other models.</td></tr> <tr valign="top"><td>eta</td> <td> The reference distance vector used for possibilistic c-means (PCM). This is set to NULL for other models.</td></tr> <tr valign="top"><td>memb</td> <td> The fuzzy membership matrix.</td></tr> <tr valign="top"><td>dist2clusters</td> <td> The matrix of object distances to cluster centers.</td></tr> </table>
返回类型vegclass以下项目：<table summary="R valueblock"> <tr valign="top"> <TD> method </ TD> <TD>的聚类分析模型的对象用于y </ TD> </ TR> <tr valign="top"> <TD>m </ TD> <TD>的模糊性指数在y</ TD > </ TR> <tr valign="top"> <TD>dnoise</ TD> <TD>距离的噪音聚类使用的噪声聚类（NC）。这是设置为NULL其他型号的。</ TD> </ TR> <tr valign="top"> <TD>eta </ TD> <TD>的参考距离矢量用于的可能性c的手段（PCM）。这是设置为NULL其他型号的。</ TD> </ TR> <tr valign="top"> <TD>memb </ TD> <TD>的模糊隶属度矩阵。 / TD> </ TR> <tr valign="top"> <TD>dist2clusters </ TD> <TD>对象的距离，聚类中心的矩阵。</ TD> </ TR> </表>
（作者）----------Author(s)----------
Miquel De C谩ceres, Forest Science Center of Catalonia.
参考文献----------References----------
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 [Related software]. Journal of Vegetation Science 21 (6): 1138-1151.
参见----------See Also----------
vegclust, as.vegclust, kmeans, cmeans, conformveg
vegclust，as.vegclust，kmeans，cmeans，conformveg
实例----------Examples----------
#Loads data (38 columns and 33 species)[数据加载（38列和33种）]
data(wetland)
dim(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)), "/"))
# Splits wetland data into two matrices of 30x27 and 11x22[湿地数据拆分成两个矩阵的30x27和11x22]
wetland.30 = wetland.chord[1:30,]
wetland.30 = wetland.30[,colSums(wetland.30)>0]
dim(wetland.30)
wetland.11 = wetland.chord[31:41,]
wetland.11 = wetland.11[,colSums(wetland.11)>0]
dim(wetland.11)
# Create noise clustering with 3 clusters from the data set with 30 sites. [创建噪音聚类有3类设置30个站点的数据。]
wetland.30.nc = vegclust(wetland.30, mobileCenters=3, m = 1.2, dnoise=0.75, method="NC", nstart=10)
# Cardinality of fuzzy clusters (i.e., the number of objects belonging to)[模糊聚类的基数（即对象的数量）]
wetland.30.nc$size
# Classifies the second set of sites according to the clustering of the first set[根据所述第一组的聚类分类的站点的第二组]
wetland.11.nc = vegclass(wetland.30.nc, wetland.11)
# Fuzzy membership matrix[模糊隶属度矩阵]
wetland.11.nc$memb
# Obtains hard membership vector, with 'N' for objects that are unclassified[获得硬会员向量，以N未分类的对象，]
defuzzify(wetland.11.nc$memb)$cluster
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 15:16:49
