plot.varSelRFBoot(varSelRF)
plot.varSelRFBoot()所属R语言包：varSelRF
plot a varSelRFBoot object
绘制varSelRFBoot对象
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Plots of out-of-bag predictions and OOB error vs. number of variables.
图袋的预测和OOB错误与数量的变量。
用法----------Usage----------
## S3 method for class 'varSelRFBoot':
plot(x, oobProb = TRUE,
oobProbBoxPlot = FALSE,
ErrorNum = TRUE,
subject.names = NULL,
class.to.plot = NULL,...)
参数----------Arguments----------
参数：x
An object of class varSelRFBoot, such as returned by function varSelRFBoot.
一个对象的类varSelRFBoot的，如返回的功能varSelRFBoot。
参数：oobProb
If TRUE plot (average) out-of-bag predictions. See prob.predictions in varSelRFBoot for more details about the out-of-bag predictions.
如果图真实袋（平均）预测。见prob.predictions在varSelRFBoot袋预测的更多详细信息。
参数：oobProbBoxPlot
If TRUE plot a box-plot of out-of-bag predictions.
如果图真实图袋一箱的预测。
参数：ErrorNum
If TRUE plot OOB error (as returned by random forest) vs. the number of variables.
如果图真实OOB错误（返回的随机森林）与变量的数量。
参数：subject.names
If not NULL, a vector, of the same length as the number of cases (samples or subjects) with IDs for the cases/samples/subjects, that will be shown to the left of the average out-of-bag prediction.
如果不为NULL，向量，情况的数量（样品或主题）的情况下，/样本/科目的ID，将要显示的左袋预测的平均长度相同的。
参数：class.to.plot
If not NULL, an integer or a vector of integers. These integers are those class levels for which out-of-bag predictions plots will be returned.
如果不为NULL，整数或整数的向量。这些整数袋预测的图将返回那些一流水平。
参数：...
Not used.
未使用。
值----------Value----------
This function is only used for its side effects of producing plots.
此功能仅用于其生产图的副作用。
警告----------Warning ----------
The OOB Error rate is biased down (and can be severely biased down) because we do (potentially many) rounds of reducing the set of predictor variables until we minimize this OOB error rate. Note, however, that this is NOT the error rate reported as the estimate of the error rate for the procedure (for which we use the
OOB错误率有失偏颇（可以严重偏见的），因为我们做许多潜在的降低轮组预测变量，直到我们这OOB错误率降到最低。然而，请注意，这不是报告的过程中的错误率估计的错误率（我们使用
注意----------Note----------
When plotting the out-of-bag predictions, we show one plot for each class. This is an overkill for two-class problems, but not necessarily for problems with more than two classes. Use class.to.plot to
当绘制袋的预测，我们为每个类的一个图。这是两个阶级一个矫枉过正的问题，但不一定适合多类的问题。使用class.to.plot
（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, summary.varSelRFBoot,
randomForest，varSelRF，summary.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：
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 14:26:23
