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=187165 (5622 observations deleted due to missingness)
## 
## node), split, n, deviance, yval
##       * denotes terminal node
## 
##  1) root 187165 13730350.0  2.338704  
##    2) humidity_3pm< 84.5 175182  5850274.0  1.528809  
##      4) humidity_3pm< 67.5 146520  2837333.0  1.004309 *
##      5) humidity_3pm>=67.5 28662  2766579.0  4.210055 *
##    3) humidity_3pm>=84.5 11983  6085324.0 14.178720  
##      6) rainfall< 27.5 10939  3655341.0 12.111930  
##       12) min_temp< 11.75 5531   681840.4  8.008968 *
##       13) min_temp>=11.75 5408  2785162.0 16.308210 *
##      7) rainfall>=27.5 1044  1893649.0 35.834480  
##       14) min_temp< 19.95 709   588138.8 26.436530 *
##       15) min_temp>=19.95 335  1110360.0 55.724480 *

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