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=187101 (5686 observations deleted due to missingness)
## 
## node), split, n, deviance, yval
##       * denotes terminal node
## 
##  1) root 187101 13637250.0   2.333881  
##    2) humidity_3pm< 83.5 174119  5581260.0   1.492223  
##      4) humidity_3pm< 67.5 146377  2881583.0   1.004715 *
##      5) humidity_3pm>=67.5 27742  2481331.0   4.064498 *
##    3) humidity_3pm>=83.5 12982  6278318.0  13.622480  
##      6) rainfall< 24.7 11712  3452853.0  11.444360  
##       12) min_temp< 11.75 5947   699981.8   7.722701 *
##       13) min_temp>=11.75 5765  2585529.0  15.283520 *
##      7) rainfall>=24.7 1270  2257490.0  33.709130  
##       14) min_temp< 22.05 1016  1019333.0  27.102850 *
##       15) min_temp>=22.05 254  1016452.0  60.134250  
##         30) max_temp>=26.75 198   475408.1  46.440400 *
##         31) max_temp< 26.75 56   372635.9 108.551800 *

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