Assignment 20
library(readxl)
data <- read_excel("C:\\Users\\RISHI RAHUL\\Desktop\\DS\\5 HClust\\Assignment\\EastWestAirlines.xlsx", sheet = "data")
data <- data[,-1]
normalized_data <- scale(data)
plot(normalized_data)
km <- kmeans(normalized_data,4) #kmeans clustering
str(km)
## List of 9
## $ cluster : int [1:3999] 1 1 1 1 4 1 4 3 2 4 ...
## $ centers : num [1:4, 1:11] -0.301 1.235 -0.138 0.631 -0.127 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:4] "1" "2" "3" "4"
## .. ..$ : chr [1:11] "Balance" "Qual_miles" "cc1_miles" "cc2_miles" ...
## $ totss : num 43978
## $ withinss : num [1:4] 7669 8242 6540 6290
## $ tot.withinss: num 28741
## $ betweenss : num 15237
## $ size : int [1:4] 2095 143 854 907
## $ iter : int 4
## $ ifault : int 0
## - attr(*, "class")= chr "kmeans"
km$centers
## Balance Qual_miles cc1_miles cc2_miles cc3_miles Bonus_miles
## 1 -0.3012579 -0.12654781 -0.5500445 0.01168634 -0.06031392 -0.5104477
## 2 1.2350103 0.56045759 0.2919732 0.18594222 1.44156994 1.0439261
## 3 -0.1382402 0.27801229 -0.2736871 0.02866055 -0.06275873 -0.2681790
## 4 0.6312966 -0.05782831 1.4821608 -0.08329518 -0.02887639 1.2669584
## Bonus_trans Flight_miles_12mo Flight_trans_12 Days_since_enroll
## 1 -0.4557152 -0.21391206 -0.235025742 -0.24159282
## 2 1.8902231 3.62256578 3.874418317 0.31598547
## 3 -0.0897408 -0.01137554 -0.001558563 0.05307777
## 4 0.8390960 -0.06633564 -0.066518056 0.45823883
## Award?
## 1 -0.7668234
## 2 0.9128067
## 3 1.2698112
## 4 0.4316923
km$cluster
## [1] 1 1 1 1 4 1 4 3 2 4 1 4 1 1 1 4 4 3 4 3 4 3 1 1 1 1 1 1 4 3 4 1 4 1
## [35] 1 4 3 1 4 3 1 4 3 4 4 3 1 3 4 1 1 1 4 3 1 1 4 3 1 4 4 1 1 1 1 2 1 4
## [69] 4 3 3 4 4 1 4 4 1 4 4 4 3 1 1 1 1 4 3 4 1 3 3 1 4 3 2 1 1 4 1 3 4 3
## [103] 1 3 1 4 2 3 4 4 4 3 2 3 3 4 1 4 4 3 1 4 4 4 4 4 4 2 3 4 3 3 3 3 3 2
## [137] 4 4 3 1 1 1 1 4 1 3 1 4 4 1 4 4 4 1 4 4 4 3 4 1 4 4 3 4 3 1 1 4 4 4
## [171] 4 1 4 3 4 4 3 3 3 3 1 3 1 3 4 1 2 1 4 1 4 2 4 1 3 1 4 4 3 4 4 3 1 4
## [205] 1 1 4 3 3 1 4 1 1 3 1 4 1 1 4 4 2 4 3 1 4 1 3 4 1 4 4 4 1 3 3 3 1 3
## [239] 2 1 4 3 4 2 4 2 1 3 4 1 1 1 4 3 3 4 4 3 1 4 1 1 1 1 3 4 1 1 4 4 4 4
## [273] 4 1 1 2 1 4 1 4 1 4 1 3 4 4 4 1 4 4 4 4 4 1 1 4 4 4 2 1 3 1 4 4 1 4
## [307] 1 2 1 1 4 4 4 4 3 3 1 1 4 3 4 4 4 2 1 3 1 2 4 1 4 1 4 3 4 4 4 1 1 4
## [341] 4 3 1 1 1 4 4 4 4 3 1 4 1 3 4 1 1 4 1 1 3 1 4 1 1 3 3 1 1 4 3 4 4 1
## [375] 3 2 1 4 1 4 2 1 4 4 2 4 1 4 4 1 1 3 3 1 1 1 1 1 1 1 1 1 1 1 2 4 1 3
## [409] 1 1 2 4 2 4 1 3 3 3 4 1 2 1 4 4 4 4 1 4 1 4 3 3 3 4 3 1 4 4 4 1 1 4
## [443] 1 1 4 3 4 1 4 1 4 1 4 4 1 1 3 1 4 4 1 4 3 1 1 4 2 4 1 3 1 2 4 1 1 2
## [477] 1 4 4 4 1 4 3 1 3 3 4 3 2 4 3 1 2 1 4 1 3 3 1 4 2 4 1 4 1 4 4 3 1 1
## [511] 4 2 4 1 4 4 3 4 4 3 1 1 4 1 3 1 4 4 4 3 3 2 4 1 4 3 3 4 1 1 1 3 1 1
## [545] 3 3 4 4 3 2 4 3 1 1 4 3 1 3 1 1 3 4 3 4 4 4 1 4 1 1 3 4 1 1 4 1 4 1
## [579] 3 1 4 1 1 1 1 1 1 4 1 3 1 1 3 4 2 1 1 1 4 4 4 4 4 4 3 3 3 1 4 1 1 2
## [613] 3 3 3 4 1 3 4 4 4 1 2 4 4 4 1 4 1 4 2 1 1 1 1 1 1 3 4 4 3 1 1 1 1 1
## [647] 1 3 1 3 3 3 3 4 1 1 1 4 3 3 4 1 2 3 4 1 1 1 1 4 4 1 4 3 4 3 3 3 4 1
## [681] 1 2 4 2 1 4 1 4 1 4 1 4 4 4 1 1 1 4 1 1 1 4 2 3 4 4 3 1 2 1 3 4 1 3
## [715] 4 1 4 3 2 1 1 3 3 4 1 4 4 1 1 1 4 4 1 1 3 1 4 1 1 4 3 4 1 3 3 4 1 1
## [749] 1 1 4 3 1 3 4 1 4 4 3 3 3 1 1 4 4 4 1 3 3 4 1 1 2 4 4 1 3 1 1 3 4 4
## [783] 3 1 1 1 1 4 4 3 3 4 4 4 1 3 4 4 4 3 4 1 1 3 1 3 4 4 1 1 1 3 4 4 4 3
## [817] 1 1 4 1 3 1 3 4 1 1 3 1 4 3 4 4 4 3 3 4 4 4 1 2 4 4 4 1 4 1 1 4 1 4
## [851] 2 2 1 1 4 4 1 1 4 4 2 4 3 1 4 4 3 1 3 3 3 3 3 1 1 3 1 4 1 1 4 4 1 4
## [885] 4 3 3 4 1 3 1 4 1 4 1 1 3 1 1 1 4 3 1 1 2 4 1 1 1 4 1 4 1 1 2 3 3 4
## [919] 1 4 1 1 4 3 1 3 3 1 1 1 4 1 4 1 4 4 4 4 3 1 3 3 3 1 1 1 4 4 3 1 1 1
## [953] 1 4 4 4 1 1 2 4 1 1 4 4 3 3 2 1 3 4 1 3 4 1 1 4 2 4 1 4 4 1 1 4 4 1
## [987] 3 1 4 1 1 3 4 4 3 4 1 4 4 4 4 3 1 4 1 1 1 3 1 4 3 1 1 3 2 3 3 4 1 1
## [1021] 4 1 3 1 1 3 1 3 1 1 1 1 2 3 1 3 4 4 1 3 1 1 4 3 3 1 3 4 4 4 1 1 4 4
## [1055] 1 4 4 4 4 1 1 2 1 3 2 3 3 4 4 1 4 4 1 1 1 1 4 1 3 3 3 1 1 3 3 4 1 3
## [1089] 1 1 1 1 1 4 3 3 3 1 1 4 1 1 4 4 1 4 4 1 3 1 4 4 4 4 1 4 1 4 1 4 1 1
## [1123] 2 4 4 4 4 1 4 1 4 3 1 1 4 3 3 1 4 1 4 3 1 4 3 3 3 3 3 1 2 1 1 1 4 3
## [1157] 1 4 4 1 3 1 1 4 3 1 1 1 4 4 3 4 4 3 3 1 4 3 4 1 1 4 3 1 1 1 4 2 4 1
## [1191] 1 1 1 4 1 1 3 1 1 1 3 1 1 1 3 1 2 3 4 1 4 1 1 3 1 4 3 1 1 3 3 4 3 1
## [1225] 4 3 4 3 1 1 1 1 3 1 1 1 2 1 1 1 3 1 1 1 2 4 1 3 1 3 4 1 3 1 4 3 3 1
## [1259] 4 1 1 3 2 1 1 3 4 3 4 4 1 3 1 4 1 1 1 3 3 1 1 4 4 4 1 4 1 1 4 3 1 3
## [1293] 3 4 3 4 1 1 2 1 2 1 3 1 1 3 4 1 1 1 4 1 1 4 2 4 3 4 1 3 1 4 3 1 1 4
## [1327] 3 4 3 3 1 1 1 1 1 1 1 3 1 4 1 1 1 1 3 1 1 3 3 1 1 3 4 4 3 1 1 3 4 1
## [1361] 1 1 3 1 4 1 1 1 1 1 3 1 4 1 3 1 1 1 4 4 1 1 4 3 4 4 3 1 3 1 1 1 1 1
## [1395] 4 3 1 4 1 1 1 4 1 1 3 4 4 3 1 1 1 4 1 4 4 3 1 3 4 4 4 1 4 3 1 4 1 1
## [1429] 2 4 4 1 1 2 1 3 4 1 4 1 3 4 1 3 1 1 3 1 1 3 4 3 4 4 1 4 1 1 1 3 1 4
## [1463] 4 4 1 1 1 3 1 3 4 4 1 1 1 1 3 4 3 4 1 4 1 4 1 1 4 1 4 2 1 1 3 3 3 1
## [1497] 4 3 3 1 3 3 1 4 1 4 1 1 1 1 1 1 3 3 1 1 3 3 3 4 3 3 1 3 3 4 4 1 1 2
## [1531] 3 1 1 3 4 1 4 1 3 4 1 1 4 1 1 3 4 2 1 1 4 1 1 1 1 1 3 3 1 1 1 1 1 1
## [1565] 1 3 1 3 3 4 1 1 1 3 1 1 3 3 1 3 1 1 1 3 3 3 1 3 3 4 1 1 4 2 1 2 3 4
## [1599] 1 3 3 1 4 1 1 4 1 1 3 1 1 1 4 4 3 4 4 1 4 4 2 1 4 2 4 1 1 1 4 1 4 1
## [1633] 4 4 1 4 1 3 1 4 1 4 4 1 1 4 1 1 1 1 4 4 1 4 1 3 4 4 3 3 3 3 4 4 1 1
## [1667] 4 3 1 3 1 4 1 4 4 3 2 1 1 3 4 4 1 4 1 1 3 4 4 3 1 4 4 3 3 3 1 1 3 3
## [1701] 3 1 4 4 1 1 4 4 1 1 4 1 1 1 1 3 3 4 4 1 1 4 4 4 4 4 1 4 2 1 4 1 3 4
## [1735] 1 1 4 1 4 1 4 1 1 1 4 1 4 1 1 1 3 4 1 4 1 1 1 1 1 1 3 1 1 4 1 4 4 3
## [1769] 1 1 1 1 3 4 4 3 1 4 1 1 1 4 1 4 3 1 4 1 1 3 1 1 1 1 3 1 1 1 3 1 3 4
## [1803] 3 4 1 3 4 1 3 1 4 1 1 1 1 3 3 4 1 4 1 1 3 1 3 1 1 1 3 1 1 1 1 3 4 1
## [1837] 1 4 4 1 4 4 4 1 1 4 2 1 4 4 1 4 1 1 1 1 1 1 3 1 4 3 1 3 4 1 1 3 3 1
## [1871] 1 4 4 1 4 1 4 4 2 1 1 4 3 1 1 2 1 1 1 1 4 1 3 4 4 1 1 1 1 4 1 1 1 1
## [1905] 1 3 1 3 1 1 4 2 1 3 1 1 4 2 1 4 4 3 3 4 3 1 1 1 1 1 2 1 1 1 4 1 4 1
## [1939] 1 4 1 4 4 4 1 1 2 1 4 4 1 3 1 1 4 3 3 1 4 1 3 3 1 1 1 3 3 1 3 1 1 1
## [1973] 1 1 4 3 1 4 1 1 3 1 1 1 1 1 1 4 1 1 1 3 4 1 1 1 1 4 3 4 1 4 4 4 2 1
## [2007] 1 1 1 4 1 3 4 1 1 2 1 1 3 4 3 4 3 1 4 3 1 1 3 1 1 1 1 4 1 3 1 4 3 3
## [2041] 1 1 1 3 1 1 4 3 1 2 3 4 3 1 1 1 3 1 2 3 1 4 3 3 1 1 3 1 3 4 4 1 4 1
## [2075] 4 1 1 1 4 1 3 1 1 3 1 1 1 4 1 1 1 3 4 3 3 1 1 3 1 1 1 3 1 1 1 4 3 3
## [2109] 1 1 1 1 4 3 3 1 1 1 3 1 1 3 3 4 1 4 1 1 1 1 3 4 4 4 3 1 4 4 1 1 1 1
## [2143] 3 1 1 4 1 3 1 1 1 2 1 2 1 1 3 3 1 1 1 3 4 4 1 1 2 3 1 4 1 3 4 4 1 3
## [2177] 3 4 1 2 3 4 3 1 1 4 4 3 1 3 1 1 1 3 3 1 4 1 3 4 1 4 3 1 3 1 3 1 1 3
## [2211] 1 3 3 3 3 1 3 2 3 1 1 1 3 1 1 2 3 1 1 1 4 1 3 1 1 1 1 1 1 1 3 3 3 4
## [2245] 1 3 4 1 1 1 2 2 4 1 3 1 1 3 1 1 1 4 1 3 3 1 3 3 1 4 3 1 4 4 3 4 4 3
## [2279] 1 1 1 3 1 4 1 1 1 4 4 1 3 1 3 3 4 4 1 3 1 1 1 3 1 1 4 4 1 4 4 3 3 4
## [2313] 1 1 1 1 4 1 4 4 1 1 3 4 1 1 1 3 3 1 1 3 4 1 4 1 3 1 3 3 1 3 1 4 3 3
## [2347] 3 1 1 1 3 4 4 1 1 4 1 4 4 4 1 1 4 1 2 1 4 3 1 1 1 1 1 3 1 2 4 1 4 3
## [2381] 1 3 1 3 1 1 1 3 1 1 3 1 4 1 1 1 1 1 3 3 1 3 4 4 1 1 1 1 1 1 1 4 3 2
## [2415] 3 1 3 4 4 1 4 1 4 1 1 3 1 3 4 1 1 1 1 1 4 4 3 4 3 3 1 4 1 4 1 4 4 1
## [2449] 2 2 1 1 4 1 4 4 4 1 3 1 1 4 4 3 1 4 1 3 1 3 1 1 4 4 4 4 1 3 1 3 1 3
## [2483] 4 1 1 1 3 4 1 4 3 1 3 3 1 1 1 1 1 3 4 3 1 3 3 3 4 1 3 3 3 1 3 4 3 1
## [2517] 1 1 3 4 1 1 2 1 1 4 4 1 3 1 1 4 3 4 3 4 1 1 1 4 1 3 1 4 1 1 1 1 4 4
## [2551] 1 1 1 3 3 1 1 3 1 4 3 4 1 1 3 1 1 3 1 1 3 1 1 3 1 1 1 1 1 4 1 1 1 3
## [2585] 1 3 3 1 1 4 1 4 1 3 4 1 1 1 1 3 3 1 1 3 4 3 1 3 4 1 3 3 4 1 3 4 1 1
## [2619] 1 1 3 3 1 1 1 3 1 1 1 1 1 1 1 3 1 3 1 3 4 4 1 1 3 1 3 3 3 4 1 1 3 4
## [2653] 1 3 1 1 2 4 1 3 1 3 1 1 1 4 1 1 1 1 4 3 2 3 4 1 1 1 1 1 1 1 3 3 3 4
## [2687] 1 1 1 3 3 3 1 4 3 1 2 1 1 1 1 1 1 1 1 1 1 3 3 2 1 4 1 1 3 4 3 1 3 1
## [2721] 1 3 3 1 1 3 3 3 4 4 4 4 3 1 1 1 1 3 3 1 4 1 3 4 1 1 1 2 1 1 1 2 3 3
## [2755] 3 1 1 1 3 1 3 3 1 1 3 1 4 1 1 1 1 4 3 3 1 2 1 1 1 1 4 1 1 4 1 1 1 1
## [2789] 1 2 1 3 3 1 3 1 1 1 1 1 1 3 2 3 1 1 4 1 1 1 1 1 1 3 1 4 1 3 1 4 4 4
## [2823] 4 3 1 1 1 1 1 3 1 4 1 1 1 3 3 1 1 4 4 1 1 1 1 3 1 1 3 4 3 1 3 4 4 3
## [2857] 3 1 1 1 1 1 3 1 3 1 3 1 1 1 3 1 3 1 1 1 1 1 3 1 1 1 4 1 1 1 1 1 2 3
## [2891] 1 3 4 1 1 4 3 3 1 4 1 3 1 2 1 4 1 1 1 1 1 1 1 3 3 1 1 1 4 3 1 1 3 1
## [2925] 1 4 1 4 1 1 1 1 4 3 4 1 1 1 4 1 1 1 3 1 1 1 1 1 1 1 3 1 1 1 3 2 3 3
## [2959] 1 1 1 1 4 1 3 1 1 3 1 3 1 1 1 1 3 1 1 1 3 1 1 1 1 3 1 4 1 3 1 1 4 1
## [2993] 3 3 4 3 3 1 1 2 3 4 4 1 1 3 3 1 1 1 1 3 1 3 4 4 4 3 3 1 4 4 1 1 1 1
## [3027] 3 3 1 1 4 2 4 1 1 3 3 3 1 1 3 1 4 3 1 1 1 1 1 3 1 4 1 3 1 1 1 3 3 1
## [3061] 1 3 4 3 1 1 1 1 1 4 3 1 1 4 1 3 4 1 1 4 3 1 2 1 3 1 1 1 1 1 1 1 3 2
## [3095] 1 1 2 1 3 1 1 3 1 4 2 2 4 1 3 1 1 1 1 4 1 1 1 1 4 3 1 1 3 1 1 1 3 4
## [3129] 1 3 1 1 1 3 1 1 4 4 3 1 1 1 1 1 1 1 4 4 4 4 1 1 1 1 4 1 3 3 3 1 2 1
## [3163] 3 1 1 2 1 3 4 3 1 3 1 3 3 3 1 3 1 1 3 1 1 3 1 4 1 1 1 1 1 1 1 3 3 1
## [3197] 1 3 1 4 1 1 1 1 1 1 1 1 3 1 1 1 3 1 4 1 1 4 3 4 1 3 1 1 1 3 1 1 1 1
## [3231] 3 1 1 1 1 2 3 3 1 1 1 3 1 1 3 1 1 1 1 2 3 1 3 1 1 3 3 1 1 1 2 4 3 3
## [3265] 1 1 1 1 1 1 3 1 1 1 1 1 1 1 4 3 1 3 2 1 1 3 1 1 1 1 3 1 1 4 3 1 1 1
## [3299] 4 1 1 1 3 1 4 1 1 1 1 3 1 4 3 1 4 4 1 1 1 1 3 1 1 1 3 1 3 1 1 4 1 3
## [3333] 3 1 1 3 3 1 2 3 3 1 1 1 1 1 4 1 1 3 1 1 4 1 3 1 4 1 1 1 1 1 4 1 1 1
## [3367] 4 1 1 3 1 1 1 1 1 3 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 4 1 3
## [3401] 1 3 1 3 1 3 1 1 1 1 1 4 1 1 1 1 1 4 1 1 1 1 1 1 4 4 1 1 1 2 1 1 1 1
## [3435] 1 1 1 1 4 1 1 1 1 1 4 1 1 4 1 1 3 1 3 1 1 1 1 1 1 1 1 3 3 2 1 1 1 3
## [3469] 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 3 4 1 1 4 3 4 1 1 3 1 1 1 4 3 1 1 4
## [3503] 1 1 1 1 1 3 3 1 1 1 1 1 1 1 1 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [3537] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 4 4
## [3571] 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 4 1 1
## [3605] 1 3 1 1 1 3 1 1 3 1 1 1 1 4 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 3 1
## [3639] 1 1 1 1 3 1 1 1 4 1 1 3 1 1 1 1 1 1 1 3 1 1 1 3 1 1 1 3 1 1 1 1 1 1
## [3673] 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [3707] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [3741] 3 1 1 1 1 1 1 1 3 1 1 3 3 4 3 3 3 1 1 1 3 3 3 1 1 1 1 1 1 4 1 1 4 1
## [3775] 1 4 1 3 1 1 1 1 3 3 4 4 1 3 2 4 1 4 4 1 1 1 4 1 3 1 3 4 1 1 3 1 3 1
## [3809] 1 1 1 3 1 1 1 1 3 1 3 4 1 1 4 4 2 1 1 1 1 3 3 3 2 1 4 1 1 3 1 1 1 1
## [3843] 1 4 1 1 2 1 1 1 1 3 1 1 1 4 3 1 1 1 4 1 3 3 1 1 1 4 1 3 1 3 1 1 1 1
## [3877] 1 3 1 1 1 4 1 4 1 1 4 1 3 1 3 1 1 1 1 1 1 3 1 4 3 1 3 1 3 1 1 2 4 1
## [3911] 1 2 1 3 1 3 1 2 1 1 1 3 1 3 1 1 1 1 1 3 4 3 3 1 2 1 3 1 1 1 1 3 1 1
## [3945] 3 1 1 1 1 1 2 1 1 3 3 1 1 1 1 1 1 1 1 1 1 1 4 1 1 1 1 1 1 3 4 1 1 1
## [3979] 3 3 1 1 1 1 1 4 1 3 1 3 1 1 1 1 3 3 3 1 1
finalmodel <- data.frame(km$cluster,data)
View(finalmodel)
x <- aggregate(data[,1:11],by=list(km$cluster),FUN=mean)
x
## Group.1 Balance Qual_miles cc1_miles cc2_miles cc3_miles Bonus_miles
## 1 1 43241.86 46.20907 1.302148 1.016229 1.000477 4817.041
## 2 2 198060.31 577.72028 2.461538 1.041958 1.293706 42356.671
## 3 3 59670.08 359.20258 1.682670 1.018735 1.000000 10668.064
## 4 4 137220.66 99.37486 4.100331 1.002205 1.006615 47743.118
## Bonus_trans Flight_miles_12mo Flight_trans_12 Days_since_enroll
## 1 7.225298 160.5341 0.4821002 3619.638
## 2 29.755245 5532.4056 16.0699301 4771.112
## 3 10.740047 444.1276 1.3676815 4228.172
## 4 19.660419 367.1720 1.1212789 5064.884
## Award?
## 1 0.0000000
## 2 0.8111888
## 3 0.9836066
## 4 0.5788313