Weighted K-means via Lloyd's algorithm
Arguments
- x
Data (or formula)
- mu
Initial centers (or number centers chosen randomly among x)
- data
optional data frmae
- weights
Optional weights
- iter.max
Max number of iterations
- n.start
Number of restarts
- init
method to create initial centres (default kmeans++)
- ...
Additional arguments to lower level functions
Examples
## Two well-separated Gaussian blobs in 2-D
set.seed(1)
x <- rbind(matrix(rnorm(100, mean = -3), ncol = 2),
matrix(rnorm(100, mean = 3), ncol = 2))
res <- wkm(x, mu = 2)
table(res$cluster)
#>
#> 1 2
#> 50 50
res$center
#> class: 1
#> [1] 2.847515 3.076869
#> ------------------------------------------------------------
#> class: 2
#> [1] -2.899552 -2.882674
## Supply explicit initial centers (as a list)
res2 <- wkm(x, mu = list(c(-3, -3), c(3, 3)))
## Weighted clustering: up-weight the second blob
w <- c(rep(1, 50), rep(10, 50))
res3 <- wkm(x, mu = 2, weights = w)
## Formula interface on a data.frame
wkm(~ Sepal.Length + Sepal.Width, data = iris, mu = 3)
#> $cluster
#> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
#> 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
#> 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
#> 3 3 3 3 3 3 3 3 3 3 2 2 2 1 2 1 2 1 2 1
#> 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
#> 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 2 2 2 1 1
#> 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
#> 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120
#> 2 1 2 2 2 2 1 2 2 2 2 2 2 1 1 2 2 2 2 1
#> 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140
#> 2 1 2 1 2 2 1 1 2 2 2 2 2 1 1 2 2 2 1 2
#> 141 142 143 144 145 146 147 148 149 150
#> 2 2 1 2 2 2 1 2 2 1
#>
#> $center
#> class: 1
#> (Intercept) Sepal.Length Sepal.Width
#> 1.000000 5.773585 2.692453
#> ------------------------------------------------------------
#> class: 2
#> (Intercept) Sepal.Length Sepal.Width
#> 1.000000 6.812766 3.074468
#> ------------------------------------------------------------
#> class: 3
#> (Intercept) Sepal.Length Sepal.Width
#> 1.000 5.006 3.428
#>
#> $ssw
#> [1] 11.3000 12.6217 13.1290
#>