Connecting(SamSPECTRAL)
Connecting()所属R语言包：SamSPECTRAL
Combines the spectral clusters to build the connected components.
结合光谱聚类建立连接的组件。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Considering some biological criterion based on density, the clusters which are identified by spectral clustering are combined to estimate biological populations.
基于密度的一些生物的标准，确定这是由谱聚类簇结合，以估计的生物种群。
用法----------Usage----------
Connecting(full, society,conductance, number.of.clusters, labels.for_num.of.clusters, separation.factor, talk=TRUE)
参数----------Arguments----------
参数：full
The matrix containing the coordinates of all data points.
矩阵包含的所有数据点的坐标。
参数：society
The list of communities.
社区名单。
参数：conductance
A matrix in which each entry is the conductance between two communities.
A矩阵中的每个条目是两族之间的电导。
参数：number.of.clusters
A list containing the desired cluster numbers.
一个列表，其中包含所需的聚类。
参数：labels.for_num.of.clusters
The k'th element of this list, is a vector containing the labels as result of clustering to k parts.
此列表的第k个元素，是一个向量，作为结果的聚类的k部分标签。
参数：separation.factor
This threshold controls to what extend clusters should be combined or kept separate.
此阈值控制到什么扩展聚类应合并或分开存放。
参数：talk
A boolean flag with default value TRUE. Setting it to FALSE will keep running the procedure quite with no messages.
一个布尔标志使用默认值true。设置为false，将继续运行程序相当没有消息。
Details
详情----------Details----------
A hint for setting separation.factor: While separation.factor=0.7 is normally an appropriate value for many datasets, for others some value in range 0.3 to 1.2 may produce better results depending on what populations are of particular interest.
一丝设置separation.factor：虽然separation.factor= 0.7对许多数据集通常是一个适当的值，为其他一些值在0.3至1.2范围可能会产生更好的结果取决于人口特别关注的是什么。
值----------Value----------
Returns two objects: 1) label, a vector containing the labels that determines to which component each data point belongs. 2) clusters.graph, the max.conductance matrix that describes the original graph based on clusters.
返回两个对象：1）标签，向量的标签，确定每个数据点属于哪个组件。 2）clusters.graph，max.conductance矩阵，描述了基于聚类上的原始图。
作者（S）----------Author(s)----------
Parisa Shooshtari and Habil Zare
参考文献----------References----------
<h3>See Also</h3> <code>SamSPECTRAL</code>
举例----------Examples----------
## Not run: [＃无法运行：]
library(SamSPECTRAL)
# Reading data file which has been transformed using log transform[读取数据文件已使用log变换转化]
data(small_data)
full <- small
# Parameters:[参数：]
m <- 3000; ns <- 200; sl <- 3; cwt <-1; precision <- 6; mnc <-30
# Sample the data and build the communities[样本数据，并建立社区]
society <- Building_Communities(full=full,m=m, space.length=sl, community.weakness.threshold=cwt)
# Compute conductance between communities[计算社区之间的电导]
conductance <- Conductance_Calculation(full=full, normal.sigma=ns, space.length=sl, society=society, precision=precision)
# Use spectral clustering to cluster the data[使用聚类数据谱聚类]
clust_result <- Civilized_Spectral_Clustering(full=full, maximum.number.of.clusters=mnc, society=society, conductance=conductance)
number.of.clusters <- clust_result@number.of.clusters
labels.for_num.of.clusters <- clust_result@labels.for_num.of.clusters
L <- labels.for_num.of.clusters[[number.of.clusters]]
# plot(full, pch='.', col= L)[图（完整，PCH =。，COL =）]
# Connect components[连接组件]
L <- Connecting(full=full, society=society, conductance=conductance, number.of.clusters=number.of.clusters,
labels.for_num.of.clusters=labels.for_num.of.clusters, separation.factor=0.39)
plot(full, pch='.', col= L)
## End(Not run)[＃结束（不运行）]
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 2012-2-26 13:50:28
