Find limits for selectboost analysis.
auto.analyze(x, ...)
# S3 method for selectboost
auto.analyze(x, ...)Numerical matrix. Selectboost object.
. Passed to the summary.selectboost function.
list of results.
plot.summary.selectboost returns an invisible list and creates four graphics.
Two plots the proportion of selection with respect to c0 (by step or according to real scale).
On the third graph, no bar means a proportion of selection less than prop.level.
Confidence intervals are computed at the conf.int.level level.
Barplot of the confidence index (1-min(c0, such that proportion|c0>conf.threshold)).
selectBoost: a general algorithm to enhance the performance of variable selection methods in correlated datasets, Frédéric Bertrand, Ismaïl Aouadi, Nicolas Jung, Raphael Carapito, Laurent Vallat, Seiamak Bahram, Myriam Maumy-Bertrand, Bioinformatics, 2020. doi:10.1093/bioinformatics/btaa855
Other Selectboost analyze functions:
plot.summary.selectboost(),
trajC0()
data(autoboost.res.x)
auto.analyze(autoboost.res.x)
#> $crit.func.values
#> c0 = 0.897 c0 = 0.532 c0 = 0.414 c0 = 0.39 c0 = 0.333 c0 = 0.291
#> 0.800 0.800 0.757 0.697 0.697 0.658 0.612
#> c0 = 0.259 c0 = 0.224 c0 = 0.185 c0 = 0.146 c0 = 0.035 c0 = 0
#> 0.594 0.532 0.524 0.511 0.499 0.471
#>
#> $crit.func.values.lim
#> crit.func.values.lim.red crit.func.values.lim.orange
#> 0.8101635 0.8539231
#> crit.func.values.lim.green
#> 0.8976827
#>
#> $force.dec
#> [1] TRUE
#>
#> $index.lim
#> index.lim.red index.lim.orange index.lim.green
#> 2 4 4
#>
#> $col.crit.func.values
#> [1] "red" "red" "orange" "orange" NA NA NA NA
#> [9] NA NA NA NA NA
#>
#> $selectboost_result.dec
#> 1 2 3 4 5 6 7 8 9 10
#> 0 1.00 1.00 1.00 1.00 0 1.00 1.00 1.00 1.00
#> c0 = 0.897 0 1.00 1.00 1.00 1.00 0 1.00 1.00 1.00 1.00
#> c0 = 0.532 0 1.00 1.00 1.00 0.89 0 1.00 0.68 1.00 1.00
#> c0 = 0.414 0 1.00 1.00 1.00 0.37 0 1.00 0.68 0.92 1.00
#> c0 = 0.39 0 1.00 1.00 1.00 0.37 0 1.00 0.68 0.92 1.00
#> c0 = 0.333 0 1.00 1.00 1.00 0.13 0 1.00 0.53 0.92 1.00
#> c0 = 0.291 0 0.92 1.00 1.00 0.13 0 1.00 0.48 0.75 0.84
#> c0 = 0.259 0 0.92 1.00 1.00 0.11 0 1.00 0.47 0.60 0.84
#> c0 = 0.224 0 0.40 1.00 1.00 0.11 0 1.00 0.47 0.55 0.79
#> c0 = 0.185 0 0.40 1.00 1.00 0.11 0 1.00 0.45 0.55 0.73
#> c0 = 0.146 0 0.40 1.00 1.00 0.11 0 1.00 0.45 0.45 0.70
#> c0 = 0.035 0 0.40 0.96 0.93 0.10 0 1.00 0.45 0.45 0.70
#> c0 = 0 0 0.37 0.93 0.90 0.06 0 0.96 0.40 0.45 0.64
#>
#> $freq.dec
#> 0 1 2 3 4 5 6 7 8 9 10 11 12 13
#> thres = 1 2 0 2 1 0 0 2 0 0 0 0 2 1 0
#> thres = 0.95 2 0 2 1 0 0 2 0 0 0 0 1 1 1
#> thres = 0.9 2 0 2 0 0 0 2 0 1 0 0 0 0 3
#> thres = 0.85 2 0 1 1 0 0 2 0 1 0 0 0 0 3
#> thres = 0.8 2 0 1 1 0 0 1 0 2 0 0 0 0 3
#> thres = 0.75 2 0 1 1 0 0 0 1 1 1 0 0 0 3
#> thres = 0.7 2 0 1 1 0 0 0 1 1 0 0 0 1 3
#> thres = 0.65 2 0 0 1 0 1 0 1 1 0 0 0 1 3
#> thres = 0.6 2 0 0 1 0 1 0 0 2 0 0 0 0 4
#> thres = 0.55 2 0 0 1 0 1 0 0 1 0 1 0 0 4
#> thres = 0.5 2 0 0 1 0 0 1 0 1 0 1 0 0 4
#> thres = 0.45 2 0 0 1 0 0 0 0 1 0 0 0 1 5
#> thres = 0.4 2 0 0 1 0 0 0 0 0 0 0 0 1 6
#> thres = 0.35 2 0 0 0 0 1 0 0 0 0 0 0 0 7
#> thres = 0.3 2 0 0 0 0 1 0 0 0 0 0 0 0 7
#> thres = 0.25 2 0 0 0 0 1 0 0 0 0 0 0 0 7
#> thres = 0.2 2 0 0 0 0 1 0 0 0 0 0 0 0 7
#> thres = 0.15 2 0 0 0 0 1 0 0 0 0 0 0 0 7
#> thres = 0.1 2 0 0 0 0 0 0 0 0 0 0 0 1 7
#> thres = 0.05 2 0 0 0 0 0 0 0 0 0 0 0 0 8
#> thres = 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10
#>
#> $freq.dec.lims
#> 0 1 2 3 4 5 6 7 8 9 10 11 12 13
#> thres = 0.810163 2 0 1 1 0 0 1 0 2 0 0 0 0 3
#> thres = 0.853923 2 0 1 1 0 0 2 0 1 0 0 0 0 3
#> thres = 0.897683 2 0 2 0 0 0 2 0 1 0 0 0 0 3
#>
#> attr(,"class")
#> [1] "summary.selectboost"
data(autoboost.res.x2)
auto.analyze(autoboost.res.x2)
#> $crit.func.values
#> c0 = 0.959 c0 = 0.37 c0 = 0.242 c0 = 0.171 c0 = 0.127 c0 = 0.097
#> 0.4218750 0.4218750 0.2706250 0.2281250 0.2212500 0.2104688 0.1923438
#> c0 = 0.073 c0 = 0.047 c0 = 0.031 c0 = 0.014 c0 = 0 c0 = 0
#> 0.1829688 0.1737500 0.1576562 0.1423438 0.1265625 0.0678125
#>
#> $crit.func.values.lim
#> crit.func.values.lim.red crit.func.values.lim.orange
#> 0.4759949 0.5263101
#> crit.func.values.lim.green
#> 0.5766253
#>
#> $force.dec
#> [1] TRUE
#>
#> $index.lim
#> index.lim.red index.lim.orange index.lim.green
#> 2 2 5
#>
#> $col.crit.func.values
#> [1] "red" "red" "green" "green" "green" NA NA NA NA
#> [10] NA NA NA NA
#>
#> $selectboost_result.dec
#> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
#> 0 1.00 1.00 1.00 1.00 0 1.00 0 1.00 1.00 1.00 1.00 0 0 0 0 0
#> c0 = 0.959 0 1.00 1.00 1.00 1.00 0 1.00 0 1.00 1.00 1.00 1.00 0 0 0 0 0
#> c0 = 0.37 0 1.00 0.97 1.00 0.88 0 0.92 0 1.00 1.00 0.32 0.97 0 0 0 0 0
#> c0 = 0.242 0 0.60 0.97 1.00 0.88 0 0.92 0 1.00 0.90 0.32 0.97 0 0 0 0 0
#> c0 = 0.171 0 0.60 0.97 0.91 0.78 0 0.92 0 1.00 0.90 0.32 0.97 0 0 0 0 0
#> c0 = 0.127 0 0.60 0.97 0.91 0.78 0 0.84 0 1.00 0.83 0.08 0.91 0 0 0 0 0
#> c0 = 0.097 0 0.60 0.97 0.88 0.78 0 0.84 0 1.00 0.83 0.00 0.73 0 0 0 0 0
#> c0 = 0.073 0 0.60 0.96 0.88 0.68 0 0.75 0 0.96 0.81 0.00 0.71 0 0 0 0 0
#> c0 = 0.047 0 0.53 0.96 0.88 0.65 0 0.46 0 0.96 0.81 0.00 0.70 0 0 0 0 0
#> c0 = 0.031 0 0.47 0.96 0.88 0.55 0 0.43 0 0.95 0.78 0.00 0.70 0 0 0 0 0
#> c0 = 0.014 0 0.34 0.95 0.88 0.55 0 0.37 0 0.89 0.78 0.00 0.61 0 0 0 0 0
#> c0 = 0 0 0.29 0.92 0.81 0.52 0 0.34 0 0.89 0.78 0.00 0.61 0 0 0 0 0
#> c0 = 0 0 0.08 0.39 0.28 0.41 0 0.34 0 0.38 0.31 0.00 0.37 0 0 0 0 0
#> 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
#> 1.00 1.00 1.00 0 1.00 0 1.00 0 0 1.00 1.00 1.00 1.00 0 1.00
#> c0 = 0.959 1.00 1.00 1.00 0 1.00 0 1.00 0 0 1.00 1.00 1.00 1.00 0 1.00
#> c0 = 0.37 0.28 0.56 1.00 0 0.72 0 0.48 0 0 0.67 0.36 0.28 0.60 0 0.52
#> c0 = 0.242 0.28 0.42 0.47 0 0.60 0 0.39 0 0 0.44 0.36 0.28 0.32 0 0.29
#> c0 = 0.171 0.28 0.42 0.47 0 0.60 0 0.39 0 0 0.36 0.36 0.28 0.24 0 0.29
#> c0 = 0.127 0.28 0.42 0.46 0 0.60 0 0.39 0 0 0.36 0.33 0.28 0.24 0 0.29
#> c0 = 0.097 0.27 0.36 0.46 0 0.59 0 0.15 0 0 0.36 0.16 0.21 0.24 0 0.29
#> c0 = 0.073 0.27 0.36 0.38 0 0.59 0 0.15 0 0 0.36 0.07 0.21 0.24 0 0.28
#> c0 = 0.047 0.26 0.36 0.38 0 0.56 0 0.15 0 0 0.36 0.01 0.20 0.16 0 0.28
#> c0 = 0.031 0.25 0.31 0.38 0 0.56 0 0.04 0 0 0.36 0.01 0.09 0.16 0 0.25
#> c0 = 0.014 0.25 0.31 0.38 0 0.56 0 0.00 0 0 0.36 0.01 0.09 0.16 0 0.22
#> c0 = 0 0.25 0.30 0.37 0 0.55 0 0.00 0 0 0.27 0.01 0.09 0.03 0 0.08
#> c0 = 0 0.25 0.28 0.07 0 0.55 0 0.00 0 0 0.02 0.01 0.00 0.03 0 0.08
#> 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
#> 1.00 1.00 0 0 1.00 0 0 0 0 0 0 0 0 1.00 0 0 0 0 1.00
#> c0 = 0.959 1.00 1.00 0 0 1.00 0 0 0 0 0 0 0 0 1.00 0 0 0 0 1.00
#> c0 = 0.37 0.36 0.55 0 0 0.44 0 0 0 0 0 0 0 0 0.77 0 0 0 0 0.72
#> c0 = 0.242 0.36 0.55 0 0 0.44 0 0 0 0 0 0 0 0 0.52 0 0 0 0 0.44
#> c0 = 0.171 0.36 0.55 0 0 0.39 0 0 0 0 0 0 0 0 0.52 0 0 0 0 0.44
#> c0 = 0.127 0.36 0.46 0 0 0.39 0 0 0 0 0 0 0 0 0.44 0 0 0 0 0.44
#> c0 = 0.097 0.32 0.43 0 0 0.36 0 0 0 0 0 0 0 0 0.44 0 0 0 0 0.44
#> c0 = 0.073 0.32 0.32 0 0 0.36 0 0 0 0 0 0 0 0 0.44 0 0 0 0 0.41
#> c0 = 0.047 0.32 0.32 0 0 0.36 0 0 0 0 0 0 0 0 0.44 0 0 0 0 0.41
#> c0 = 0.031 0.05 0.32 0 0 0.25 0 0 0 0 0 0 0 0 0.41 0 0 0 0 0.38
#> c0 = 0.014 0.05 0.32 0 0 0.10 0 0 0 0 0 0 0 0 0.19 0 0 0 0 0.26
#> c0 = 0 0.00 0.21 0 0 0.03 0 0 0 0 0 0 0 0 0.19 0 0 0 0 0.14
#> c0 = 0 0.00 0.00 0 0 0.03 0 0 0 0 0 0 0 0 0.00 0 0 0 0 0.14
#> 52 53 54 55 56 57 58 59 60 61 62 63 64
#> 1.00 0 0 0 0 1.00 0 0 1.00 0 0 0 0
#> c0 = 0.959 1.00 0 0 0 0 1.00 0 0 1.00 0 0 0 0
#> c0 = 0.37 0.16 0 0 0 0 0.47 0 0 0.32 0 0 0 0
#> c0 = 0.242 0.16 0 0 0 0 0.40 0 0 0.32 0 0 0 0
#> c0 = 0.171 0.16 0 0 0 0 0.40 0 0 0.28 0 0 0 0
#> c0 = 0.127 0.15 0 0 0 0 0.38 0 0 0.28 0 0 0 0
#> c0 = 0.097 0.00 0 0 0 0 0.33 0 0 0.27 0 0 0 0
#> c0 = 0.073 0.00 0 0 0 0 0.33 0 0 0.27 0 0 0 0
#> c0 = 0.047 0.00 0 0 0 0 0.33 0 0 0.27 0 0 0 0
#> c0 = 0.031 0.00 0 0 0 0 0.33 0 0 0.22 0 0 0 0
#> c0 = 0.014 0.00 0 0 0 0 0.26 0 0 0.22 0 0 0 0
#> c0 = 0 0.00 0 0 0 0 0.20 0 0 0.22 0 0 0 0
#> c0 = 0 0.00 0 0 0 0 0.20 0 0 0.12 0 0 0 0
#>
#> $freq.dec
#> 0 1 2 3 4 5 6 7 8 9 10 11 12 13
#> thres = 1 37 0 22 3 1 0 0 1 0 0 0 0 0 0
#> thres = 0.95 37 0 20 3 1 1 0 0 0 0 1 1 0 0
#> thres = 0.9 37 0 19 2 0 2 2 0 0 0 1 0 1 0
#> thres = 0.85 37 0 18 2 1 2 1 0 0 0 0 1 2 0
#> thres = 0.8 37 0 18 2 1 0 1 1 0 1 0 0 3 0
#> thres = 0.75 37 0 17 3 0 0 1 1 1 0 0 0 4 0
#> thres = 0.7 37 0 15 5 0 0 0 1 1 0 1 0 4 0
#> thres = 0.65 37 0 14 6 0 0 0 0 1 1 1 0 4 0
#> thres = 0.6 37 0 13 5 0 0 1 0 2 1 0 0 5 0
#> thres = 0.55 37 0 11 6 0 1 0 0 2 1 0 0 5 1
#> thres = 0.5 37 0 10 6 0 2 0 0 1 1 0 0 6 1
#> thres = 0.45 37 0 8 7 0 1 1 1 0 1 1 0 6 1
#> thres = 0.4 37 0 7 3 2 1 1 2 0 1 3 0 5 2
#> thres = 0.35 37 0 5 2 0 1 3 1 0 2 3 2 3 5
#> thres = 0.3 37 0 3 1 2 1 2 0 0 2 3 3 3 7
#> thres = 0.25 37 0 1 0 1 1 3 0 0 2 3 3 3 10
#> thres = 0.2 37 0 1 0 0 1 2 0 1 2 2 2 5 11
#> thres = 0.15 37 0 0 0 0 1 1 1 0 3 1 3 6 11
#> thres = 0.1 37 0 0 0 0 1 1 1 0 3 0 3 5 13
#> thres = 0.05 37 0 0 0 0 0 2 0 1 1 0 3 4 16
#> thres = 0 0 0 0 0 0 0 0 0 0 0 0 0 0 64
#>
#> $freq.dec.lims
#> 0 1 2 3 4 5 6 7 8 9 10 11 12 13
#> thres = 0.475995 37 0 9 7 0 2 0 0 1 1 0 0 6 1
#> thres = 0.52631 37 0 11 6 0 1 0 0 1 1 0 1 5 1
#> thres = 0.576625 37 0 13 5 0 0 0 0 3 1 0 0 5 0
#>
#> attr(,"class")
#> [1] "summary.selectboost"