分類木の管理

Rで学ぶSupervised Learning:分類

Brett Lantz

Instructor

事前枝刈り

MaxDepthによる早期停止

MinSplitによる早期停止

Rで学ぶSupervised Learning:分類

事後枝刈り

複雑な枝の枝刈り

誤差と複雑度のプロット

Rで学ぶSupervised Learning:分類

Rによる事前・事後枝刈り

# pre-pruning with rpart
library(rpart)
prune_control <- rpart.control(maxdepth = 30, minsplit = 20)

m <- rpart(repaid ~ credit_score + request_amt,
           data = loans,
           method = "class",
           control = prune_control)
# post-pruning with rpart
m <- rpart(repaid ~ credit_score + request_amt,
           data = loans,
           method = "class")

plotcp(m)

m_pruned <- prune(m, cp = 0.20)
Rで学ぶSupervised Learning:分類

さあ、練習しましょう!

Rで学ぶSupervised Learning:分類

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