R语言模型评估网格搜索

### 网格搜索 ###
install.packages("gbm")
set.seed(1234)
library(caret)
library(gbm)
fitControl <- trainControl(method = 'repeatedcv',number = 10,repeats = 5)
# 设置网格搜索的参数池
gbmGrid <- expand.grid(interaction.depth = c(3,5,9),n.trees = (1:20)*5,shrinkage = 0.1,n.minobsinnode = 20)
nrow(gbmGrid)
# 训练模型，找出最优参数组合
gbmfit <- train(accept ~ .,data = car,method = 'gbm',trControl = fitControl,tuneGrid = gbmGrid,metric = 'Accuracy')gbmfit$bestTune # 查看模型最优的参数组合plot(gbmfit)

     8        0.5290             nan     0.1000    0.06389        0.4866             nan     0.1000    0.066810        0.4438             nan     0.1000    0.050620