x <- runif(50)
x
## [1] 0.68797257 0.16353036 0.48562868 0.72862508 0.37146905 0.36017922
## [7] 0.77299841 0.54519149 0.01167801 0.84158615 0.40999795 0.72051187
## [13] 0.93889678 0.49847704 0.54013292 0.69945387 0.10299072 0.28591339
## [19] 0.67139810 0.85243128 0.58522177 0.27546235 0.90805681 0.37375106
## [25] 0.61585376 0.01760247 0.14459245 0.85527970 0.98343393 0.93343293
## [31] 0.19879899 0.04787605 0.78606321 0.09061294 0.24775883 0.16757205
## [37] 0.09028047 0.05394046 0.41835479 0.85100369 0.10176805 0.77904192
## [43] 0.79670848 0.68561378 0.09598251 0.94090917 0.07649988 0.49657666
## [49] 0.06046043 0.05820715
y <- runif(50)
y
## [1] 0.08379858 0.17816054 0.49383789 0.06863478 0.50760897 0.97573041
## [7] 0.41614894 0.15243164 0.84474612 0.46428225 0.54594203 0.27029002
## [13] 0.62445839 0.90029050 0.99716969 0.49287545 0.65800555 0.58685371
## [19] 0.03703294 0.83228408 0.55754268 0.61885467 0.18250468 0.82488745
## [25] 0.61672753 0.38632574 0.54593841 0.41154203 0.52674306 0.76197866
## [31] 0.74818813 0.84730775 0.82992709 0.82583815 0.99612485 0.51017971
## [37] 0.34349826 0.63497258 0.42082052 0.47071120 0.13952046 0.17052566
## [43] 0.46247065 0.25123798 0.79036288 0.83681037 0.72707024 0.54121563
## [49] 0.89626193 0.95377853
data <- cbind(x,y)
data
## x y
## [1,] 0.68797257 0.08379858
## [2,] 0.16353036 0.17816054
## [3,] 0.48562868 0.49383789
## [4,] 0.72862508 0.06863478
## [5,] 0.37146905 0.50760897
## [6,] 0.36017922 0.97573041
## [7,] 0.77299841 0.41614894
## [8,] 0.54519149 0.15243164
## [9,] 0.01167801 0.84474612
## [10,] 0.84158615 0.46428225
## [11,] 0.40999795 0.54594203
## [12,] 0.72051187 0.27029002
## [13,] 0.93889678 0.62445839
## [14,] 0.49847704 0.90029050
## [15,] 0.54013292 0.99716969
## [16,] 0.69945387 0.49287545
## [17,] 0.10299072 0.65800555
## [18,] 0.28591339 0.58685371
## [19,] 0.67139810 0.03703294
## [20,] 0.85243128 0.83228408
## [21,] 0.58522177 0.55754268
## [22,] 0.27546235 0.61885467
## [23,] 0.90805681 0.18250468
## [24,] 0.37375106 0.82488745
## [25,] 0.61585376 0.61672753
## [26,] 0.01760247 0.38632574
## [27,] 0.14459245 0.54593841
## [28,] 0.85527970 0.41154203
## [29,] 0.98343393 0.52674306
## [30,] 0.93343293 0.76197866
## [31,] 0.19879899 0.74818813
## [32,] 0.04787605 0.84730775
## [33,] 0.78606321 0.82992709
## [34,] 0.09061294 0.82583815
## [35,] 0.24775883 0.99612485
## [36,] 0.16757205 0.51017971
## [37,] 0.09028047 0.34349826
## [38,] 0.05394046 0.63497258
## [39,] 0.41835479 0.42082052
## [40,] 0.85100369 0.47071120
## [41,] 0.10176805 0.13952046
## [42,] 0.77904192 0.17052566
## [43,] 0.79670848 0.46247065
## [44,] 0.68561378 0.25123798
## [45,] 0.09598251 0.79036288
## [46,] 0.94090917 0.83681037
## [47,] 0.07649988 0.72707024
## [48,] 0.49657666 0.54121563
## [49,] 0.06046043 0.89626193
## [50,] 0.05820715 0.95377853
dim(data)
## [1] 50 2
View(data)
windows()
plot(data)
plot(data, type = "n")
text(data, rownames(data))
km <- kmeans(data, 4)
km$cluster
## [1] 3 4 4 3 4 1 3 3 1 3 4 3 2 2 2 3 1 4 3 2 2 4 3 1 2 4 4 3 3 2 1 1 2 1 1
## [36] 4 4 1 4 3 4 3 3 3 1 2 1 4 1 1
str(km)
## List of 9
## $ cluster : int [1:50] 3 4 4 3 4 1 3 3 1 3 ...
## $ centers : num [1:4, 1:2] 0.137 0.743 0.768 0.264 0.825 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ : chr [1:4] "1" "2" "3" "4"
## .. ..$ : chr [1:2] "x" "y"
## $ totss : num 8.46
## $ withinss : num [1:4] 0.328 0.44 0.59 0.581
## $ tot.withinss: num 1.94
## $ betweenss : num 6.52
## $ size : int [1:4] 13 9 15 13
## $ iter : int 3
## $ ifault : int 0
## - attr(*, "class")= chr "kmeans"
windows()
km$centers
## x y
## 1 0.1368259 0.8248673
## 2 0.7434910 0.7730210
## 3 0.7684584 0.2974153
## 4 0.2637499 0.4475967
cluster <- as.data.frame(km$cluster)
final <- cbind(cluster, data)
final
## km$cluster x y
## 1 3 0.68797257 0.08379858
## 2 4 0.16353036 0.17816054
## 3 4 0.48562868 0.49383789
## 4 3 0.72862508 0.06863478
## 5 4 0.37146905 0.50760897
## 6 1 0.36017922 0.97573041
## 7 3 0.77299841 0.41614894
## 8 3 0.54519149 0.15243164
## 9 1 0.01167801 0.84474612
## 10 3 0.84158615 0.46428225
## 11 4 0.40999795 0.54594203
## 12 3 0.72051187 0.27029002
## 13 2 0.93889678 0.62445839
## 14 2 0.49847704 0.90029050
## 15 2 0.54013292 0.99716969
## 16 3 0.69945387 0.49287545
## 17 1 0.10299072 0.65800555
## 18 4 0.28591339 0.58685371
## 19 3 0.67139810 0.03703294
## 20 2 0.85243128 0.83228408
## 21 2 0.58522177 0.55754268
## 22 4 0.27546235 0.61885467
## 23 3 0.90805681 0.18250468
## 24 1 0.37375106 0.82488745
## 25 2 0.61585376 0.61672753
## 26 4 0.01760247 0.38632574
## 27 4 0.14459245 0.54593841
## 28 3 0.85527970 0.41154203
## 29 3 0.98343393 0.52674306
## 30 2 0.93343293 0.76197866
## 31 1 0.19879899 0.74818813
## 32 1 0.04787605 0.84730775
## 33 2 0.78606321 0.82992709
## 34 1 0.09061294 0.82583815
## 35 1 0.24775883 0.99612485
## 36 4 0.16757205 0.51017971
## 37 4 0.09028047 0.34349826
## 38 1 0.05394046 0.63497258
## 39 4 0.41835479 0.42082052
## 40 3 0.85100369 0.47071120
## 41 4 0.10176805 0.13952046
## 42 3 0.77904192 0.17052566
## 43 3 0.79670848 0.46247065
## 44 3 0.68561378 0.25123798
## 45 1 0.09598251 0.79036288
## 46 2 0.94090917 0.83681037
## 47 1 0.07649988 0.72707024
## 48 4 0.49657666 0.54121563
## 49 1 0.06046043 0.89626193
## 50 1 0.05820715 0.95377853
View(final)