defuzzify(vegclust)
defuzzify()所属R语言包：vegclust
Defuzzifies a fuzzy partition
Defuzzifies一个模糊的分区
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Transforms a fuzzy classification into a crisp (hard) classification.
一个清晰的分类（硬）把一个模糊的划分。
用法----------Usage----------
defuzzify(object, method = "max", alpha = 0.5, na.rm = FALSE)
参数----------Arguments----------
参数：object
A site-by-group fuzzy membership matrix. Alternatively, an object of class 'vegclust' or 'vegclass'.
一个网站组的模糊隶属度矩阵。可替换地，一个对象的类的vegclust或vegclass。
参数：method
Either "max" to choose for the maximum membership value across clusters, or "cut" for an alpha-cut.
无论是"max"选择在聚类中的最大隶属度值，或"cut"α-切割。
参数：alpha
Threshold for the alpha-cut, bounded between 0 and 1.
为α-切割，包括位于0和1之间的范围内的阈值。
参数：na.rm
If TRUE removes the objects that do not belong to any cluster when using method="cut".
如果TRUE删除的对象不属于任何聚类时使用method="cut"。
Details
详细信息----------Details----------
Alpha-cut means that memberships lower than alpha are transformed into 0 while memberships higher than alpha are transformed into 1. This means that if alpha values are low (i.e. close to 0), an object may belong to more than one group after defuzzification. These will generate a concatenation of cluster names in the output cluster vector and a row with sum more than one in the memb matrix). Similarly, if alpha is high (i.e. close to 1) there are objects that may be left unclassified. These will get NA in the cluster vector and zero row in the memb matrix.
籍低于α-α-切割装置，被转换成0，而转化为1籍比α高。这意味着，如果alpha值低（即接近0），一个对象可能多属于后一组模糊化。这将产生一个串联的聚类名称cluster数额超过1memb矩阵，向量和行输出）。同样，如果α为高（即接近1）有可能会留下未分类的对象。这将得到NAcluster行memb矩阵向量和零。
值----------Value----------
A list with the following items: <table summary="R valueblock"> <tr valign="top"><td>memb</td> <td> A data frame with the hard membership partition.</td></tr> <tr valign="top"><td>cluster</td> <td> A vector (factor) with the name of the cluster for each object.</td></tr> </table>
以下项目：<table summary="R valueblock"> <tr valign="top"> <TD> memb</ TD> <td>一个数据框与成员硬盘分区。</列表TD> </ TR> <tr valign="top"> <TD> cluster</ TD> <td>一个向量（因子）与聚类中的每个对象的名称。</ TD> </ TR> </ TABLE>
（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.
参见----------See Also----------
cmeans, vegclust
cmeans，vegclust
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 = 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]
wetland.nc = vegclust(wetland.chord, mobileCenters=3, m = 1.2, dnoise=0.75, method="NC", nstart=10)
# Defuzzification using an alpha-cut (alpha=0.5)[去模糊化，使用的α-切割（α= 0.5）]
wetland.nc.df = defuzzify(wetland.nc$memb, method="cut")
# Cluster vector, with 'N' for objects that are unclassified, and 'NA' for objects that are intermediate[聚类的向量，N是未分类的对象，“NA”的对象是中间]
print(wetland.nc.df$cluster)
# Hard membership matrix (site 22 does not get any cluster assigned)[硬隶属度矩阵（22期没有得到任何聚类分配）]
print(wetland.nc.df$memb)
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。
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发表于 2012-10-1 15:16:15
