summary.varSelRFBoot(varSelRF)
summary.varSelRFBoot()所属R语言包：varSelRF
Summary of a varSelRFBoot object
摘要一个varSelRFBoot对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Returns error rate and stability measures of a varSelRFBoot object.
返回错误率和稳定性的措施的一个varSelRFBoot的对象。
用法----------Usage----------
## S3 method for class 'varSelRFBoot':
summary(object, return.model.freqs = FALSE,
return.class.probs = TRUE,
return.var.freqs.b.models = TRUE, ...)
参数----------Arguments----------
参数：object
An object of class varSelRFBoot, as returned from varSelRFBoot.
一个对象的类varSelRFBoot的，返回varSelRFBoot。
参数：return.model.freqs
If TRUE return a table with the frequencies of the final "models" (sets of selected variables) over all bootstrap replications.
如果返回true表最后的“模式”（设置选定的变量）的所有引导复制的频率。
参数：return.class.probs
If TRUE return average class probabilities for each sample based on the out-of-bag probabilites (see varSelRFBoot, the prob.predictions component).
如果返回true每班平均每个样品的概率基础上的OUT袋probabilites的（见varSelRFBoot，prob.predictions部件）。
参数：return.var.freqs.b.models
If TRUE return the frequencies of all variables selected from the bootstrap replicates.
如果返回true选择从引导的所有变量的频率重复。
参数：...
Not used.
未使用。
值----------Value----------
If return.class.probs = TRUE a matrix with the average class probabilities for each sample based on the out-of-bag probabilites.
如果return.class.probs = TRUE矩阵的平均类基于的袋probabilites中的每个样本的概率。
Regardless of that setting, print out several summaries: <table summary="R valueblock"> <tr valign="top"><td>Summaries related to the "simplified" random forest on the original data</td> <td> Such as the number and identity of the variables selected.</td></tr> <tr valign="top"><td>Summaries related to the error rate estimate</td> <td> Such as the .632+ estimate, and some of its components</td></tr> <tr valign="top"><td>Summaries related to the stability (uniqueness) of the results obtained</td> <td> Such as the frequency of the selected variables in the bootstrap runs, the frequency of the selected variables in the boostrap runs that are also among the variables selected from the complete run, the overlap of the bootstrap forests with the forest from the original data set (see varSelRF for the definition of overlap), and (optionally) the frequency of the "models", where a model is the set of variables selected in any particular run.</td></tr> </table>
不管该设置，打印出摘要：<table summary="R valueblock"> <tr valign="top"> <TD> Summaries related to the "simplified" random forest on the original data</ TD> <TD>这样的数量和身份选择的变量。</ TD> </ TR> <tr valign="top"> <TD>Summaries related to the error rate estimate </ TD> <TD>如0.632 +估计，和它的一些组件</ TD > </ TR> <tr valign="top"> <TD>Summaries related to the stability (uniqueness) of the results obtained </ TD> <TD>如在引导所选变量的运行频率，频率的所选变量的自举也选自完整的运行产生的变量的运行中，从原始数据集（见varSelRF的定义的重叠）的自举森林与森林重叠，和（可选）的频率“模型“，其中一种模式是选择在任何特定的应用程序运行的一组变量。</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Ramon Diaz-Uriarte <a href="mailto:rdiaz02@gmail.com">rdiaz02@gmail.com</a>
参考文献----------References----------
Breiman, L. (2001) Random forests. Machine Learning, 45, 5–32.
Diaz-Uriarte, R. and Alvarez de Andres, S. (2005) Variable selection from random forests: application to gene expression data. Tech. report. http://ligarto.org/rdiaz/Papers/rfVS/randomForestVarSel.html
Efron, B. & Tibshirani, R. J. (1997) Improvements on cross-validation: the .632+ bootstrap method. J. American Statistical Association, 92, 548–560.
参见----------See Also----------
randomForest, varSelRF, varSelRFBoot, plot.varSelRFBoot,
randomForest，varSelRF，varSelRFBoot，plot.varSelRFBoot，
实例----------Examples----------
## Not run: [＃不运行：]
## This is a small example, but can take some time.[＃这是一个小例子，但可能需要一些时间。]
x <- matrix(rnorm(25 * 30), ncol = 30)
x[1:10, 1:2] <- x[1:10, 1:2] + 2
cl <- factor(c(rep("A", 10), rep("B", 15)))
rf.vs1 <- varSelRF(x, cl, ntree = 200, ntreeIterat = 100,
vars.drop.frac = 0.2)
rf.vsb <- varSelRFBoot(x, cl,
bootnumber = 10,
usingCluster = FALSE,
srf = rf.vs1)
rf.vsb
summary(rf.vsb)
plot(rf.vsb)
## End(Not run)[＃（不执行）]
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注：
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发表于 2012-10-1 14:26:51
