Description Usage Arguments Value Author(s) Examples

This function performs cross-entropy clustering on a data matrix.
It is based on `cec`

but is limited to 2D matrices and
implements its own splitting process.

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`x` |
A numeric matrix with two columns. |

`centers` |
Either a matrix of initial centers or the number of initial centers. |

`iter.max` |
Maximum number of iterations at each clustering. |

`split` |
Enables split mode. This mode discovers new clusters after initial clustering, by trying to split single clusters into two. |

`split.width` |
The maximum authorized width of a cluster. If a cluster is
wider than |

`split.height` |
The maximum authorized height of a cluster. If a cluster
is higher than |

`split.density` |
The minimum authorized density of a cluster. If a
cluster is less dense than |

`min.size` |
The minimum authorized size (in number of items) of a cluster.
If a cluster is smaller than |

`split.sensitivity` |
The minimum amount of improvement in the cost function of the cross-entropy clustering for a splitting event to be considered valid. |

A matrix with 6 columns: x and y coordinates of the centers of the clusters, width, height, and angle of the covariance ellipse best describing each cluster, and the number of element in each cluster.

Simon Garnier, garnier@njit.edu

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