Description Usage Arguments Details Value Note Author(s) References See Also Examples

Function `ADEC`

performs which the functions ADECa, ADECb and ADECc
is specified by the user.

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`List` |
A list of data matrices of the same type. It is assumed the rows are corresponding with the objects. |

`distmeasure` |
The distance measure to be used on the fused data matrix (character). Should be one of "tanimoto", "euclidean", "jaccard","hamming". |

`normalize` |
Logical. Indicates whether to normalize the distance matrices or not.
This is recommended if different distance types are used. More details
on normalization in |

`method` |
A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names. |

`t` |
The number of iterations. |

`r` |
Optional. The number of features to take for the random sample. |

`nrclusters` |
The number of clusters to cut the dendrogram in. If a sequence is specified either ADECb or ADECc is performed. A fixed number of clusters defaults to ADECa |

`clust` |
Choice of clustering function (character). Defaults to "agnes". |

`linkage` |
Choice of inter group dissimilarity (character). Defaults to "ward". |

`alpha` |
The parameter alpha to be used in the "flexible" linkage of the agnes function. Defaults to 0.625 and is only used if the linkage is set to "flexible" |

`ResampleFeatures` |
Logical. Whether the features should be resamples. If TRUE, either ADECa or ADECc is performed. |

See the details of ADECa, ADECb and ADEDc for more information.

The returned value is a list with the following three elements.

`AllData` |
Fused data matrix of the data matrices |

`S` |
The resulting co-association matrix |

`Clust` |
The resulting clustering |

The value has class 'ADEC'. The Clust element will be of interest for further applications.

For now, only hierarchical clustering with the `agnes`

function implemented.

Marijke Van Moerbeke

FODEH, J. S., BRANDT, C., LUONG, B. T., HADDAD, A., SCHULTZ, M., MURPHY, T., KRAUTHAMMER, M. (2013). Complementary Ensemble Clustering of Biomedical Data. J Biomed Inform. 46(3) pp.436-443.

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