classify(clst)
classify()所属R语言包：clst
classify
分类
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Functions to perform classification by local similarity threshold.
执行当地的相似性阈值分类的功能。
用法----------Usage----------
classify(dmat, groups, dvect, method = "mutinfo", minScore = 0.45,
doffset = 0.5, dStart = NA, maxDepth = 10, minGroupSize = 2,
objNames = names(dvect), keep.data = TRUE, ..., verbose =
FALSE)
classifyIter(dmat, groupTab, dvect, dStart = NA, multiple = FALSE,
keep.data = TRUE, ..., verbose = FALSE)
classifier(dmat, groups, dvect, method = 'mutinfo', minScore = 0.45,
doffset = 0.5, dStart = NA, minGroupSize = 2,
objNames = names(dvect), keep.data = TRUE, ..., verbose = FALSE,
depth = 1)
pull(dmat, groups, index)
pullTab(dmat, groupTab, index)
参数----------Arguments----------
参数：dmat
Square matrix of pairwise distances.
成对距离方阵。
参数：groups
Object coercible to a factor identifying group membership of objects corresponding to either edge of dmat.
对象强制转换的一个因素确定相应的要么dmat边缘的对象组成员。
参数：groupTab
a data.frame representing a taxonomy, with columns in increasing order of specificity from left to right (ie, Kingdom –> Species). Column names are used to name taxonomic ranks. Rows correspond to margins of dmat.
数据框代表一个分类，增加特异性从左至右的顺序（即王国“ - >”种“）中的列。列名用来命名分类行列。行对应DMAT利润率。
参数：dvect
numeric vector of distance from query sequence to each reference corresponding to margins of dmat.
数字矢量距离从查询序列每个参考相应DMAT利润率。
参数：method
The method for calculating the threshold; only 'mutinfo' is currently implemented.
阈值的计算方法;只有mutinfo“目前正在实施。
参数：minScore
Threshold value for the match score to define a match.
比赛得分来定义匹配的阈值。
参数：doffset
Offset used in the denominator of the expression to calculate match score to penalize very small groups of reference objects.
用于抵消中表达的分母计算比赛得分惩罚非常小团体的参考对象。
参数：dStart
start with this value of D.
与此值D开始。
参数：multiple
if TRUE, stops at the rank that yields at least one match; if FALSE, continues to perform classification until exactly one match is identified.
如果为TRUE，停止产生至少有一个匹配的排名，如果为FALSE，将继续执行，直到完全确定一个匹配的分类。
参数：maxDepth
Maximum number of iterations that will be attempted to perform classification.
将尝试进行分类的迭代的最大数量。
参数：minGroupSize
The minimal number of members comprising at least one group required to attempt classification.
数量最少的成员组成一组至少需要尝试分类。
参数：objNames
Optional character identifiers for objects corresponding to margin of dmat.
可选字符识别的对象相应的保证金dmat。
参数：keep.data
Populates thresh$distances (see findThreshold) if TRUE.
填充thresh$distances（见findThreshold）如果为true。
参数：verbose
Terminal output is produced if TRUE.
如果为TRUE端子输出产生。
参数：index
an integer specifying an element in dmat
一个整数，指定dmat元素
参数：...
see Details
查看详细信息
参数：depth
specifies iteration number (not meant to be user-defined)
指定迭代次数（并非被用户定义）
Details
详情----------Details----------
classify performs iterative classification. See the vignette vignette for package clst for a description of the classification algorithm.
classify执行迭代分类。看到包分类算法的描述clst暗角暗角。
classifier performs non-iterative classification, and is typically not called directly by the user.
classifier执行非迭代分类，通常不是由用户直接调用。
The functions pull and pullTab are used to remove a single element of dmat for the purpose of performing classification agains the remaining elements. The value of these two functions (a list) can be passed directly to classify or classifyIter directly (see examples).
职能pull和pullTab是用来删除一个单一的元素dmat防止家庭进行分类的目的，剩余的元素。这两个函数（列表）的价值，可以通过直接classify或classifyIter直接（见例子）。
值----------Value----------
classify and classifyIter return x, a list of lists, one for each iteration of the classifier. Each sub-list contains the following named elements:
classify和classifyIter回报x，一个列表，为每个迭代的分类之一。每个子列表包含以下元素：
参数：depth
An integer indicating the number of the iteration (where x[[i]]$depth == i)
一个整数，表示迭代次数（其中x [我] $深度==我）
参数：tally
a data.frame with one row for each group or reference objects. Columns below and above contain counts of reference objects with distance values greater than or less than D, respectively; score, containing match score S; match is 1 if S ≥ minScore, 0 otherwise; and the minimum, median, and maximum values of distances to all members of the indicated group.
data.frame一排每个组或参考对象。列below和above包含的参考对象的距离大于或大于D值分别计数;score，包含比赛得分S;match 1，如果S ≥ minScore，否则为0;和指定组的所有成员的距离最小，中位数和最大值。
参数：details
a list of two matrices, named "below" and "above", itemizing each object with index i in the reference set with distances below or above the distance threshold D, respectively. Columns include index, the index i; dist, the distance between the object and the query; and group, indicating the classification of the object.
一个名为“以下”，“上面”的两个矩阵，列表，逐项说明指数低于或高于距离阈值ð距离，分别设置参考我的每个对象。列包括index指数;dist，对象和查询之间的距离; group，表示对象的分类。
参数：matches
Character vector naming groups to which query object belongs.
特征向量的命名查询对象所属的团体，。
参数：thresh
object returned by findThreshold
返回的对象findThreshold
参数：params
a list of input arguments and their values
输入参数的名单和他们的价值观
参数：input
list containing copies of dvect and groups
列表中包含dvect和groups副本
作者（S）----------Author(s)----------
Noah Hoffman
参见----------See Also----------
findThreshold
findThreshold
举例----------Examples----------
## illustrate classification using the Iris data set[＃说明使用Iris数据集分类]
data(iris)
dmat <- as.matrix(dist(iris[,1:4], method="euclidean"))
groups <- iris$Species
## remove one element from the data set and perform classification using[＃从数据集删除一个元素，并进行分类使用]
## the remaining elements as the reference set[＃作为参考集的其余元素]
ind <- 1
cat(paste('class of "unknown" sample is Iris',groups[ind]),fill=TRUE)
cc <- classify(dmat[-ind,-ind], groups[-ind], dvect=dmat[ind, -ind])
printClst(cc)
## this operation can be performed conveinetly using the `pull` function[＃执行此操作可以使用拉功能conveinetly]
ind <- 51
cat(paste('class of "unknown" sample is Iris',groups[ind]),fill=TRUE)
cc <- do.call(classify, pull(dmat, groups, ind))
printClst(cc)
str(cc)
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 2012-2-25 15:13:07
