Description Usage Arguments Value

Loss function for max-margin clustering

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`x` |
numeric matrix representing the dataset (one sample per row) |

`k` |
an integer specifying number of clusters to find |

`minClusterSize` |
an integer vector specifying the minimum number of sample per cluster. Given values are reclycled if necessary to have one value per cluster. |

`groups` |
a logical matrix for instance grouping (groups[i,j] TRUE when sample i belong to group j). |

`minGroupOverlap` |
an integer matrix specifyng the minimum number of instance per cluster for each group. |

`weight` |
a weight vector for each instance |

the loss function to optimize for max margin clustering of the given dataset

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