library(tree)
## Warning: package 'tree' was built under R version 4.3.1
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.3.2
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
wine_clustering <- read.csv("C:/Users/Mauri/Downloads/wine-clustering.csv")
train <- sample(seq(length(wine_clustering$Alcohol)), length(wine_clustering$Alcohol) * 0.7, replace = FALSE)
wine.tree <- tree(wine_clustering$Alcohol ~ Color_Intensity, wine_clustering, subset = train)
plot(wine.tree)
text(wine.tree, pretty = 0)
wine.tree
## node), split, n, deviance, yval
## * denotes terminal node
##
## 1) root 124 78.5100 13.03
## 2) Color_Intensity < 3.46 37 8.0410 12.18 *
## 3) Color_Intensity > 3.46 87 32.0500 13.40
## 6) Color_Intensity < 4.65 24 5.6820 13.13 *
## 7) Color_Intensity > 4.65 63 24.0300 13.50
## 14) Color_Intensity < 7 35 13.1700 13.63
## 28) Color_Intensity < 6.05 25 11.3800 13.52
## 56) Color_Intensity < 5.465 14 6.5560 13.73 *
## 57) Color_Intensity > 5.465 11 3.3990 13.25 *
## 29) Color_Intensity > 6.05 10 0.7598 13.90 *
## 15) Color_Intensity > 7 28 9.5410 13.34
## 30) Color_Intensity < 7.675 9 2.0500 13.05 *
## 31) Color_Intensity > 7.675 19 6.4220 13.47 *
test <- setdiff(seq(length(wine_clustering$Alcohol)), train)
tree.pred <- predict(wine.tree, wine_clustering[test, ])
summary(tree.pred)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 12.18 12.18 13.13 13.00 13.47 13.90
result_table <- with(wine_clustering[test, ], table(tree.pred, Alcohol))
print(result_table)
## Alcohol
## tree.pred 11.56 11.61 11.62 11.64 11.66 11.76 11.79 11.81 12 12.04
## 12.1789189189189 0 1 1 1 0 0 1 1 1 1
## 13.0511111111111 0 0 0 0 0 0 0 0 0 0
## 13.1295833333333 0 0 0 0 1 1 0 0 0 0
## 13.2481818181818 1 0 0 0 0 0 0 0 0 0
## 13.4694736842105 0 0 0 0 0 0 0 0 0 0
## 13.7285714285714 0 0 0 0 0 0 0 0 0 0
## 13.898 0 0 0 0 0 0 0 0 0 0
## Alcohol
## tree.pred 12.08 12.25 12.29 12.37 12.42 12.43 12.45 12.47 12.51 12.52
## 12.1789189189189 1 1 2 0 2 0 0 1 0 1
## 13.0511111111111 0 0 0 0 0 0 1 0 0 0
## 13.1295833333333 0 0 0 1 0 1 0 0 0 0
## 13.2481818181818 0 0 0 0 0 0 0 0 0 0
## 13.4694736842105 0 0 0 0 0 0 0 0 0 0
## 13.7285714285714 0 0 0 1 0 0 0 0 1 0
## 13.898 0 0 0 0 0 0 0 0 0 0
## Alcohol
## tree.pred 12.69 12.7 12.77 12.84 12.85 12.88 12.93 13.07 13.27 13.3
## 12.1789189189189 1 0 1 0 0 0 0 0 0 0
## 13.0511111111111 0 0 0 0 0 0 0 0 0 0
## 13.1295833333333 0 0 0 0 1 0 1 1 0 1
## 13.2481818181818 0 0 0 0 0 0 0 0 0 0
## 13.4694736842105 0 0 0 0 0 0 0 0 1 0
## 13.7285714285714 0 1 0 1 0 1 0 0 0 0
## 13.898 0 0 0 0 0 0 0 0 0 0
## Alcohol
## tree.pred 13.32 13.39 13.45 13.49 13.62 13.64 13.69 13.72 13.73 13.76
## 12.1789189189189 0 0 0 0 0 0 0 0 0 0
## 13.0511111111111 0 0 0 0 0 0 0 0 0 0
## 13.1295833333333 0 0 0 0 1 0 0 0 0 0
## 13.2481818181818 0 0 0 1 0 0 1 0 1 0
## 13.4694736842105 1 0 1 0 0 0 0 0 0 0
## 13.7285714285714 0 1 0 0 0 1 0 0 0 1
## 13.898 0 0 0 0 0 0 0 1 0 0
## Alcohol
## tree.pred 13.77 13.82 13.84 13.86 13.94 14.06 14.12 14.21 14.23 14.38
## 12.1789189189189 0 0 0 1 0 0 0 0 0 0
## 13.0511111111111 0 1 0 0 0 0 0 0 0 1
## 13.1295833333333 0 0 0 0 0 0 0 0 0 0
## 13.2481818181818 0 0 0 0 0 1 0 0 1 0
## 13.4694736842105 0 0 1 0 1 0 0 0 0 0
## 13.7285714285714 0 0 0 0 0 0 1 1 0 0
## 13.898 1 0 0 0 0 0 0 0 0 0
## Alcohol
## tree.pred 14.39
## 12.1789189189189 0
## 13.0511111111111 0
## 13.1295833333333 0
## 13.2481818181818 0
## 13.4694736842105 0
## 13.7285714285714 1
## 13.898 0