s22150110
s22150110
Recently Published
アイリスの種類
setosa versicolor virginica
1 0 0.9074074 0.09259259 because Petal.Length >= 2.5 & Petal.Width < 1.8
versicolor 90％以上
自転車
気温が12度以上
湿度が85度以下
Plot
d <- read.csv('https://stats.dip.jp/01_ds/data/Mall_Customers.csv')
colnames(d) <- c('id', 'gender', 'age', 'income', 'score')
library(DT)
datatable(d, options = list(pageLength = 5))
NGROUPS <- 5
matplot(x = d$income, y = d$score, pch = 16, type = 'p')
grid()
# カラーパレット
COL <- rainbow(NGROUPS)
km <- kmeans(d[, c('income','score')],centers = NGROUPS, nstart = 25)
c <- vector('list', NGROUPS)
matplot(x = d$income, y = d$score, pch = 16, type = 'p', col = COL[1:NGROUPS] )
grid()
for (i in 1:NGROUPS)
{
c[[i]] <- d[km$cluster == i, ]
matpoints(x = c[[i]]$income,
y = c[[i]]$score,
pch = 16,
col = COL[i])
}
legend('topright', pch = 16, bg='white', col = COL[1:NGROUPS], legend = paste0('Group',1:NGROUPS))
VIF課題
library(DT)
d <- read.csv('https://stats.dip.jp/01_ds/data/car_mileage.csv')
datatable(d)
library(car)
lm1 <- lm(燃費~気筒数+馬力+車体重量+加速性能, data=d)
summary(lm1)
(v <- vif(lm1))
barplot(v, main = 'VIF')
