20.74 Regression Trees

The discussion so far has dwelt on classification trees. Regression trees are similarly well catered for in R.

We can plot regression trees as with classification trees, but the node information will be different and some options will not make sense. For example, extra= only makes sense for 100 and 101.

First we will build regression tree:

target <- "risk_mm"
vars <- c(inputs, target)
form <- formula(paste(target, "~ ."))
(model <- rpart(formula=form, data=ds[tr, vars]))

## n=141892 (4054 observations deleted due to missingness)
## 
## node), split, n, deviance, yval
##       * denotes terminal node
## 
##  1) root 141892 10136960  2.299120  
##    2) humidity_3pm< 84.5 132975  4530675  1.519646  
##      4) humidity_3pm< 68.5 113539  2283099  1.039171 *
##      5) humidity_3pm>=68.5 19436  2068247  4.326430 *
##    3) humidity_3pm>=84.5 8917  4320662 13.923060  
##      6) rainfall< 27.9 8173  2446015 11.837640  
##       12) min_temp< 18.55 6704  1245281  9.940453 *
##       13) min_temp>=18.55 1469  1066485 20.495710 *
##      7) rainfall>=27.9 744  1448642 36.831850  
##       14) min_temp< 17.65 359   218956 23.629530 *
##       15) min_temp>=17.65 385  1108763 49.142600 *

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