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More from Akifumi Eguchi (19)
Randomforestで高次元の変数重要度を見る #japanr LT
- 9. どうやって使うの?caretのすがた
library(ranger)
library(caret)
library(mlbench)
data(Sonar, package="mlbench")
train.x = data.matrix(Sonar[train.ind, 1:60])
train.y = Sonar[train.ind, 61]
tr = trainControl(method = "repeatedcv”, number = 5, repeats = 5)
grid = expand.grid(mtry = 1:20)
set.seed(71)
ranger_fit = train(train.x, train.y, method = "ranger",
tuneGrid = grid, trControl=tr, importance = "permutaAon")
importance_pvalues(ranger_fit$finalModel, method = "janitza",
conf.level = 0.95)
- 17. どうやって使うの?vitaのすがた
hTps://cran.r-project.org/web/packages/vita/index.html
randomforestとvita packageを組み合わせて使うのが普通だが、
ranger内に関数が用意されてて早くて楽なので今回はそっちを使う
Vita packageの場合の使い方
cv_vi = CVPVI(X,y,k = 2,mtry = 3,
ntree = 1000,ncores = 4)
cv_p = NTA(cv_vi$cv_varim)
summary(cv_p,pless = 0.1)
cl.rf = randomForest(X,y,mtry = 3,ntree =
500, importance = TRUE)
pvi_p = NTA(importance(cl.rf, type=1,
scale=FALSE))
summary(pvi_p)
または