Description Usage Arguments Details Value References See Also Examples
Performes a repeated cross validation analysis and computes the probability of selection for each variable.
1 | AUCRFcv(x, nCV = 5, M = 20)
|
x |
an object of class |
nCV |
number of folds in cross validation. By default a 5-fold cross validation is performed. |
M |
number of cross validation repetitions. |
The results of this repeated cross validation analysis are (1) a corrected estimation
of the predictive accuracy of the selected variables and (2) an estimate of the probability of selection for
each variable.
The AUC-RF algorithm is exhaustively described in Calle et. al.(2011).
The same AUCRF
object passed (see AUCRF
) as argument but updated with the following
components:
cvAUC |
mean of AUC values in test datasets of the optimal sets of predictors. |
Psel |
probability of selection of each variable as the proportion of times that is selected by AUC-RF method. |
Calle ML, Urrea V, Boulesteix A-L, Malats N (2011) "AUC-RF: A new strategy for genomic profiling with Random Forest". Human Heredity. (In press)
OptimalSet
, AUCRF
, randomForest
.
1 2 3 4 5 6 7 8 9 10 11 12 13 |
Loading required package: randomForest
randomForest 4.6-12
Type rfNews() to see new features/changes/bug fixes.
AUCRF 1.1
Number of selected variables: Kopt= 32
AUC of selected variables: OOB-AUCopt= 0.7787711
AUC from cross validation: 0.759109
Importance Measure: MDG
Selected.Variables Importance Prob.Select
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
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