View source: R/CC_without_robScore_functions.R

multi_kmeans_gen | R Documentation |

Multiple K-means generation

```
multi_kmeans_gen(X, rep = 10, range.k = c(2, 5), method = "random")
```

`X` |
input data Nsample x Nfeatures |

`rep` |
number of repeats |

`range.k` |
vector of minimum and maximum values for k |

`method` |
method for the choice of k at each repeat |

At each repeat, k is selected randomly or based on the best silhouette width from a discrete uniform distribution between range.k[1] and range.k[2]. Then k-means clustering is applied and result is returned.

matrix of clusterings Nsample x Nrepeat

```
X = gaussian_clusters()$X
Clusters = multi_kmeans_gen(X)
```

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