Description Usage Arguments Value Examples

For each observation the euclidean distance to each of the cluster centres is calculated and cluster with the smallest distance is return for that observation.

1 | ```
nearest_cluster(data, centres)
``` |

`data` |
a matrix (n x m) to be clustered |

`centres` |
matrix of cluster means (k x m), wher k is the number of clusters. |

vector of cluster allocations, n values ranging from 1 to k.

1 2 3 | ```
iris_mat <- as.matrix(iris[,1:4])
centres<- tkmeans(iris_mat, 3 , 0.2, c(1,1,1,1), 1, 10, 0.001)
nearest_cluster(iris_mat, centres)
``` |

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