Description Usage Arguments Value Author(s) Examples

A recursive (not acutally implemented as recursion) partitioning of data into two disjoint sets at every level as described in https://en.wikipedia.org/wiki/Hierarchical_clustering

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`data` |
Data file name on disk (NUMA optmized) or In memory data matrix |

`kmax` |
The maximum number of centers |

`nrow` |
The number of samples in the dataset |

`ncol` |
The number of features in the dataset |

`iter.max` |
The maximum number of iteration of k-means to perform |

`nthread` |
The number of parallel threads to run |

`init` |
The type of initialization to use c("forgy") or initial centers |

`tolerance` |
The convergence tolerance for k-means at each hierarchical split |

`dist.type` |
What dissimilarity metric to use |

`min.clust.size` |
The minimum size of a cluster when it cannot be split |

A list of lists containing the attributes of the output.
cluster: A vector of integers (from 1:**k**) indicating the cluster to
which each point is allocated.
centers: A matrix of cluster centres.
size: The number of points in each cluster.
iter: The number of (outer) iterations.

Disa Mhembere <[email protected]>

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clusternor documentation built on May 2, 2019, 11:36 a.m.

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