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lrns = list(
% h6 V2 w5 T5 d7 o4 t* R; K( E: ~ makeLearner("classif.lda", id = "lda"),, D+ ]2 w/ v( H" c1 v9 K5 `
makeLearner("classif.rpart", id = "rpart"),# b; A: y( J0 O; S1 g9 g
makeLearner("classif.randomForest", id = "randomForest")) S; V! z) [. b5 R$ r2 _ \
)+ r8 W2 S! G% g1 a
$ v* K7 e- ]+ C3 Y( O0 n3 j! p
## Get additional Tasks from package mlbench
9 [. w7 b% ^3 m1 m. c- iring.task = convertMLBenchObjToTask("mlbench.ringnorm", n = 10)
, c c, [" q$ \' Q& t# Lwave.task = convertMLBenchObjToTask("mlbench.waveform", n = 10)
% [" ?- b% B, E3 r# U
: Z: A8 S" w) J/ h* v( Z' w0 d3 Mtasks = list(iris.task, sonar.task, pid.task, ring.task, wave.task) I+ Q3 [# t4 ]
rdesc = makeResampleDesc("CV", iters = 3)
5 M( Q/ J' L; Q: l) Lmeas = list(mmce, ber, timetrain)
9 F; `2 K5 j& T/ b5 wbmr = benchmark(lrns, tasks, rdesc, meas, show.info = FALSE)9 }8 v8 g2 x+ U" d% ]
bmr
5 ]4 C2 s" `# |plotBMRBoxplots(bmr, measure = ber, style = "violin", pretty.names = FALSE) + l, R% T4 Z/ n
aes(color = learner.id) +
0 V4 P# N# D- W. p" l theme(strip.text.x = element_text(size = 8)) |
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