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lrns = list(" V a; M" ~" B: P
makeLearner("classif.lda", id = "lda"),6 F5 s) w4 E: }! G- `+ p" L
makeLearner("classif.rpart", id = "rpart"),( G/ s3 {. y" a
makeLearner("classif.randomForest", id = "randomForest")+ D9 I& A7 X/ o+ D( J
)
4 _2 K' B! F( R9 e& U% E) k4 h" B8 _7 n% J
## Get additional Tasks from package mlbench
$ ]7 K+ i! X$ v8 z- ?ring.task = convertMLBenchObjToTask("mlbench.ringnorm", n = 10). ^) O1 M0 R# ?
wave.task = convertMLBenchObjToTask("mlbench.waveform", n = 10)5 I. ?2 R( @' u1 l m: B
- f7 y$ A/ i2 w. F atasks = list(iris.task, sonar.task, pid.task, ring.task, wave.task)7 J, S: [$ l+ G' {5 E9 u
rdesc = makeResampleDesc("CV", iters = 3). n" o' Y8 ?. Z, v& F
meas = list(mmce, ber, timetrain). z. j# {0 _+ m' @
bmr = benchmark(lrns, tasks, rdesc, meas, show.info = FALSE)
+ E! c' x. C# n" {* x* N' rbmr
/ @, C* d! {! i; cplotBMRBoxplots(bmr, measure = ber, style = "violin", pretty.names = FALSE) +
- A) R' I3 V% N8 O3 V6 C2 l& x aes(color = learner.id) +$ [+ M: |: w1 W- Y+ H
theme(strip.text.x = element_text(size = 8)) |
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