d <- read.csv('https://stats.dip.jp/01_ds/data/bike_rental.csv')
library(DT)
datatable(d,options = list(pageLength = 5))
COL <- c(rgb(255, 0, 0, 105, max = 255), # 赤
rgb( 0, 0, 255, 105, max = 255), # 青
rgb( 0, 155, 0, 105, max = 255), # 緑
rgb(100, 100, 100, 55, max = 255)) # 灰
library(rpart)
library(rpart.plot)
tree <- rpart(レンタル数~ 季節+月+ 祝日+ 曜日+ 休日+天気 + 気温+ 湿度+風速,
data = d, method = 'anova', cp = 0.02)
rpart.plot(tree, type = 5)
tree <- rpart(レンタル数~ 季節+月+ 祝日+ 曜日+ 休日+天気 + 気温+ 湿度+風速,
data = d, method = 'anova',cp= 0.01)
rpart.rules(tree, type = 5)
## Warning: rpart.rules: ignoring argument 'type'
## レンタル数
## 1663 when 気温 < 4.1 & 季節 is 春 or 冬
## 2261 when 気温 is 4.1 to 12.3 & 湿度 >= 68 & 季節 is 春 or 冬
## 2723 when 気温 is 4.1 to 7.8 & 湿度 < 68 & 季節 is 春 or 冬
## 3382 when 気温 >= 12.3 & 湿度 >= 85
## 3941 when 気温 is 7.8 to 12.3 & 湿度 < 68 & 季節 is 春 or 冬
## 4176 when 気温 < 12.3 & 季節 is 秋
## 4626 when 気温 >= 12.3 & 湿度 is 69 to 85 & 風速 >= 12
## 4966 when 気温 is 12.3 to 17.1 & 湿度 < 69 & 月 < 9
## 5644 when 気温 >= 12.3 & 湿度 is 69 to 85 & 風速 < 12
## 5885 when 気温 >= 17.1 & 湿度 < 69 & 月 < 9
## 6615 when 気温 >= 12.3 & 湿度 < 69 & 月 >= 9
rpart.plot(tree, branch.type = 5)
plotcp(tree)
tree2 <- prune(tree, cp = 0.1)
rpart.plot(tree2, branch.type = 5)
tree3 <- prune(tree, cp = 0.01)
rpart.plot(tree3, branch.type = 5)
kableExtra::kable(rpart.rules(tree3,cover = T))
| 8 |
1663 |
when |
気温 |
< |
4.1 |
|
|
|
|
|
|
|
|
& |
季節 |
is |
春 or 冬 |
|
|
|
|
|
|
|
|
9% |
| 18 |
2261 |
when |
気温 |
is |
4.1 |
to |
12.3 |
& |
湿度 |
>= |
|
|
68 |
& |
季節 |
is |
春 or 冬 |
|
|
|
|
|
|
|
|
6% |
| 38 |
2723 |
when |
気温 |
is |
4.1 |
to |
7.8 |
& |
湿度 |
< |
68 |
|
|
& |
季節 |
is |
春 or 冬 |
|
|
|
|
|
|
|
|
7% |
| 6 |
3382 |
when |
気温 |
>= |
|
|
12.3 |
& |
湿度 |
>= |
|
|
85 |
|
|
|
|
|
|
|
|
|
|
|
|
4% |
| 39 |
3941 |
when |
気温 |
is |
7.8 |
to |
12.3 |
& |
湿度 |
< |
68 |
|
|
& |
季節 |
is |
春 or 冬 |
|
|
|
|
|
|
|
|
4% |
| 5 |
4176 |
when |
気温 |
< |
12.3 |
|
|
|
|
|
|
|
|
& |
季節 |
is |
秋 |
|
|
|
|
|
|
|
|
14% |
| 28 |
4626 |
when |
気温 |
>= |
|
|
12.3 |
& |
湿度 |
is |
69 |
to |
85 |
|
|
|
|
|
|
|
|
& |
風速 |
>= |
12 |
8% |
| 60 |
4966 |
when |
気温 |
is |
12.3 |
to |
17.1 |
& |
湿度 |
< |
69 |
|
|
|
|
|
|
& |
月 |
< |
9 |
|
|
|
|
6% |
| 29 |
5644 |
when |
気温 |
>= |
|
|
12.3 |
& |
湿度 |
is |
69 |
to |
85 |
|
|
|
|
|
|
|
|
& |
風速 |
< |
12 |
10% |
| 61 |
5885 |
when |
気温 |
>= |
|
|
17.1 |
& |
湿度 |
< |
69 |
|
|
|
|
|
|
& |
月 |
< |
9 |
|
|
|
|
24% |
| 31 |
6615 |
when |
気温 |
>= |
|
|
12.3 |
& |
湿度 |
< |
69 |
|
|
|
|
|
|
& |
月 |
>= |
9 |
|
|
|
|
7% |
d2 <- read.csv('https://stats.dip.jp/01_ds/data/iris.csv')
DT::datatable(d2,options = list(pageLength = 5))
library(rpart)
library(rpart.plot)
tree4 <- rpart(Species~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width,
data = d2, method = 'class',cp= 0.005)
rpart.plot(tree4, type = 5)
rpart.rules(tree4, cover = T)
## Species seto vers virg cover
## setosa [1.00 .00 .00] when Petal.Length < 2.5 33%
## versicolor [ .00 .91 .09] when Petal.Length >= 2.5 & Petal.Width < 1.8 36%
## virginica [ .00 .02 .98] when Petal.Length >= 2.5 & Petal.Width >= 1.8 31%
rpart.plot(tree4, branch.type = 5)
plotcp(tree4)
tree5 <- prune(tree4, cp = 0.005)
rpart.plot(tree5, branch.type = 5)
kableExtra::kable(rpart.rules(tree5,cover = T))
| 2 |
setosa |
[1.00 .00 .00] |
when |
Petal.Length |
< |
2.5 |
|
|
|
|
33% |
| 6 |
versicolor |
[ .00 .91 .09] |
when |
Petal.Length |
>= |
2.5 |
& |
Petal.Width |
< |
1.8 |
36% |
| 7 |
virginica |
[ .00 .02 .98] |
when |
Petal.Length |
>= |
2.5 |
& |
Petal.Width |
>= |
1.8 |
31% |
d.new <- data.frame(Sepal.Length = 4.0,
Sepal.Width = 3.0,
Petal.Length = 3.0,
Petal.Width = 1.0
)
rpart.predict(tree4, newdata = d.new)
## setosa versicolor virginica
## 1 0 0.9074074 0.09259259