Using the Decision Tree on the Weather Dataset

library(rattle)

## Warning: package 'rattle' was built under R version 4.2.1

## Loading required package: tibble

## Loading required package: bitops

## Rattle: A free graphical interface for data science with R.
## Version 5.5.1 Copyright (c) 2006-2021 Togaware Pty Ltd.
## Type 'rattle()' to shake, rattle, and roll your data.

library(rpart)

## Warning: package 'rpart' was built under R version 4.2.1

weatherDS <- new.env()
evalq({
  data <- weather
  nobs <- nrow(data)
  vars <- -grep('^(Date|Locat|RISK)', names(weather))
}, weatherDS)
evalq({
  set.seed(42)
  train <- sample(nobs, 0.7*nobs)
}, weatherDS)
evalq({
  form <- formula(RainTomorrow ~.)
  
}, weatherDS)
weatherRPART <- new.env(parent=weatherDS)

set.seed(41)
evalq({
  control <- rpart.control(cp=0, minbucket=0)
  model <- rpart(formula=form,
                 data=data[train, vars],
                 control=control)
}, weatherRPART)
print(weatherRPART$model$cptable)

##            CP nsplit  rel error    xerror      xstd
## 1 0.119047619      0 1.00000000 1.0000000 0.1410790
## 2 0.095238095      2 0.76190476 1.0714286 0.1450034
## 3 0.047619048      3 0.66666667 0.9761905 0.1397146
## 4 0.035714286      8 0.40476190 1.0238095 0.1424147
## 5 0.031746032     10 0.33333333 1.0238095 0.1424147
## 6 0.023809524     13 0.23809524 1.0476190 0.1437226
## 7 0.011904762     19 0.09523810 1.2380952 0.1532666
## 8 0.007936508     25 0.02380952 1.2857143 0.1554187
## 9 0.000000000     28 0.00000000 1.3571429 0.1584874

plotcp(weatherRPART$model)
grid()