`vimix.Rd`

Variational Bayesian inference for unsupervised clustering

vimix(X, K, prior, indep = F, init = "kmeans", select = F, tol = 1e-09, maxiter = 2000, verbose = F)

X | NxD data matrix. |
---|---|

K | (Maximum) number of clusters. |

prior | Prior parameters (optional). |

indep | Booleand indicator. If TRUE, the features are considered to be independent. Default is FALSE. |

init | Initialisation method (optional). If it is a vector, it is interpreted as the vector of initial cluster allocations. If it is a string, it is interpreted as the name of the clustering algorithm used for the initialisation (only "kmeans" and "random") available at the moment). |

select | Boolean flag. If TRUE, variable selection is used. Default is FALSE. |

tol | Tolerance on lower bound. Default is 10e-20. |

maxiter | Maximum number of iterations of the VB algorithm. Default is 2000. |

verbose | Boolean flag which, if TRUE, prints the iteration numbers. Default is FALSE. |

A list containing L, the lower bound at each step of the algorithm, label, a vector containing the cluster labels, model, a list containing the trained model structure.

Bishop, C.M., 2006. Pattern recognition and machine learning. Springer.