R语言 随机森林回归

主要利用R语言进行随机森林回归，还有其他两种回归， library(lattice) library(grid) library(DMwR) library(rpart) library(ipred) library(randomForest) #回归树，装袋算法，随机森林三大回归 #前二种算法可以计算缺失数据，但随机森林不行，所以还需将数据进行清洗整理 data(algae) algae <- algae[-manyNAs(algae,0.2), ]#占有20%的NA值的行去掉 clean.algae <- knnImputation(algae,k=10)#平均值填充NA值 #回归树模型计算 model.tree=rpart(a1 ~ ., data = clean.algae[, 1:12]) summary(model.tree) pre.tree <- predict(model.tree, clean.algae) plot(pre.tree~clean.algae$a1) nmse1 <- mean((pre.tree- clean.algae[,'a1'])^2)/mean((mean(clean.algae[,'a1'])- clean.algae[,'a1'])^2) nmse1