AUCRF optimal set selection.

Description

Returns the optimal set of predictive variables selected by the AUC-RF method.

Usage

   OptimalSet(object)

Arguments

Value

A data.frame with the selected variables ordered by the initial ranking, their importance values (initial ranking) and, if available, the probability of selection value measured by AUCRFcv function.

See Also

AUCRF, AUCRFcv.

Examples

  data(fitCV)
  OptimalSet(fitCV)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(AUCRF)
Loading required package: randomForest
randomForest 4.6-12
Type rfNews() to see new features/changes/bug fixes.
AUCRF 1.1
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AUCRF/OptimalSet.Rd_%03d_medium.png", width=480, height=480)
> ### Name: OptimalSet
> ### Title: AUCRF optimal set selection.
> ### Aliases: OptimalSet
> 
> ### ** Examples
> 
>   data(fitCV)
>   OptimalSet(fitCV)
     Name Importance Prob.Selection
1    SNP9  15.047305           1.00
2    SNP4  12.912120           1.00
3    SNP3  10.486599           1.00
4    SNP7   9.767075           1.00
5    SNP8   9.283819           1.00
6    SNP2   9.043039           1.00
7    SNP6   8.743129           1.00
8   SNP10   8.465736           1.00
9    SNP5   7.844703           1.00
10   SNP1   7.533021           1.00
11 SNP369   2.677609           0.35
12 SNP584   2.565316           0.19
13 SNP747   2.504847           0.09
14  SNP47   2.469360           0.26
15  SNP55   2.469196           0.14
16 SNP674   2.445041           0.24
17 SNP354   2.441501           0.04
18 SNP993   2.424503           0.16
19 SNP661   2.423057           0.51
20  SNP73   2.399690           0.03
21 SNP690   2.398267           0.56
22  SNP14   2.390978           0.05
23 SNP878   2.387848           0.50
24 SNP651   2.353301           0.00
25 SNP191   2.349521           0.36
26 SNP684   2.346010           0.16
27 SNP278   2.341461           0.06
28 SNP771   2.336632           0.04
29 SNP575   2.318485           0.71
30 SNP544   2.307716           0.61
31 SNP726   2.299561           0.13
32 SNP336   2.279044           0.07
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>