mtcars data set
data("mtcars")
colnames(mtcars)
## [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"
## [11] "carb"
mtcars3<-mtcars[,1:3]
mtcarsk3<-kmeans(mtcars3,centers=3)
mtcarsk3$size
## [1] 8 16 8
mtcarsk3$centers
## mpg cyl disp
## 1 14.6000 8.000 399.1250
## 2 24.5000 4.625 122.2937
## 3 16.7625 7.500 279.1750
mtcarsk3$cluster
## Mazda RX4 Mazda RX4 Wag Datsun 710
## 2 2 2
## Hornet 4 Drive Hornet Sportabout Valiant
## 3 1 3
## Duster 360 Merc 240D Merc 230
## 1 2 2
## Merc 280 Merc 280C Merc 450SE
## 2 2 3
## Merc 450SL Merc 450SLC Cadillac Fleetwood
## 3 3 1
## Lincoln Continental Chrysler Imperial Fiat 128
## 1 1 2
## Honda Civic Toyota Corolla Toyota Corona
## 2 2 2
## Dodge Challenger AMC Javelin Camaro Z28
## 3 3 1
## Pontiac Firebird Fiat X1-9 Porsche 914-2
## 1 2 2
## Lotus Europa Ford Pantera L Ferrari Dino
## 2 1 2
## Maserati Bora Volvo 142E
## 3 2
plot.new()
selectedData <- mtcars[, c("mpg","qsec")]
clusters <- kmeans(selectedData, 3)
plot(x=selectedData[,1], y=selectedData[,2],
col = mtcarsk3$cluster,
pch = 20, cex = 3,
main = paste("qsec", "vs.", "mpg"),
xlab = "mpg",
ylab = "qsec")
points(mtcarsk3$centers, pch = 4, cex = 2, lwd = 4)
abline(lm(selectedData[,2] ~ selectedData[,1]))
