qpPrecisionRecall(qpgraph)
qpPrecisionRecall()所属R语言包：qpgraph
Calculation of precision-recall curves
的精密召回曲线的计算
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Calculates the precision-recall curve (see Fawcett, 2006) for a given measure of association between all pairs of variables in a matrix.
计算精密召回曲线的协会给所有对矩阵中的变量之间的措施（看到福西特，2006年）。
用法----------Usage----------
qpPrecisionRecall(measurementsMatrix, refGraph, decreasing=TRUE, pairup.i=NULL,
pairup.j=NULL, recallSteps=c(seq(0,0.1,0.005),seq(0.2,1.0,0.1)))
参数----------Arguments----------
参数：measurementsMatrix
matrix containing the measure of association between all pairs of variables.
矩阵包含对所有变量之间的关联措施。
参数：refGraph
a reference graph from which to calculate the precision-recall curve provided either as an adjacency matrix, a two-column matrix of edges, a graphNEL-class object or a graphAM-class object.
从该计算精密召回曲线，提供一个参考图的邻接矩阵，两列矩阵的边缘，一个graphNEL-class对象或graphAM-class对象。
参数：decreasing
logical; if TRUE then the measurements are ordered in decreasing order; if FALSE then in increasing order.
逻辑;如果为TRUE，然后测量递减顺序排序，如果为FALSE，然后在递增顺序。
参数：pairup.i
subset of vertices to pair up with subset pairup.j.
顶点子集的子集pairup.j配对。
参数：pairup.j
subset of vertices to pair up with subset pairup.i.
顶点子集的子集pairup.i配对。
参数：recallSteps
steps of the recall on which to calculate precision.
召回的步骤来计算的精度。
Details
详情----------Details----------
The measurementsMatrix should be symmetric and may have also contain NA values which will not be taken into account. That is an alternative way to restricting the variable pairs with the parameters pairup.i and pairup.j.
measurementsMatrix应该是对称的，可能也包含NA值不会考虑。这是另一种方式限制变量对参数pairup.i和pairup.j。
值----------Value----------
A matrix where rows correspond to recall steps and columns correspond, respetively, to the actual recall, the precision, the number of true positives at that recall rate and the threshold score that yields that recall rate.
行对应召回步骤和列对应的，respetively，实际召回，精度，真阳性的数量，召回率和阈值的得分的一个矩阵，其中，收益率，召回率。
作者（S）----------Author(s)----------
R. Castelo and A. Roverato
参考文献----------References----------
Pattern Recogn. Lett., 27:861-874, 2006.
参见----------See Also----------
qpPRscoreThreshold qpGraph qpAvgNrr qpPCC
qpPRscoreThresholdqpGraphqpAvgNrrqpPCC
举例----------Examples----------
require(mvtnorm)
nVar <- 50 ## number of variables[＃变量]
maxCon <- 5 ## maximum connectivity per variable[＃最大连接每个变量]
nObs <- 30 ## number of observations to simulate[＃号观测到模拟]
set.seed(123)
A <- qpRndGraph(p=nVar, d=maxCon)
Sigma <- qpG2Sigma(A, rho=0.5)
X <- rmvnorm(nObs, sigma=as.matrix(Sigma))
## estimate non-rejection rates[＃估计非排斥反应发生率。]
nrr.estimates <- qpNrr(X, q=5, verbose=FALSE)
## estimate Pearson correlation coefficients[＃估计Pearson相关系数]
pcc.estimates <- qpPCC(X)
## calculate area under the precision-recall curve[＃计算精度召回曲线下的面积]
## for both sets of estimated values of association[＃两套协会的估计值]
nrr.prerec <- qpPrecisionRecall(nrr.estimates, refGraph=A, decreasing=FALSE,
recallSteps=seq(0, 1, 0.1))
f <- approxfun(nrr.prerec[, c("Recall", "Precision")])
integrate(f, 0, 1)$value
pcc.prerec <- qpPrecisionRecall(abs(pcc.estimates$R), refGraph=A,
recallSteps=seq(0, 1, 0.1))
f <- approxfun(pcc.prerec[, c("Recall", "Precision")])
integrate(f, 0, 1)$value
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 11:41:02
