Description Usage Arguments Details Value Author(s) See Also

Given a treeClust object, or the necessary components, compute all pairwise dissimilarities for input to a clustering algorithm

1 |

`obj` |
Object of class treeClust |

`d.num` |
Method of dissimilarities computation. See "Details". |

`tbl` |
Two-column of information about trees. Always included in a treeClust object, but may be supplied separately. Required if d.num = 2 or 4. |

`mat` |
Matrix of leaf-membership factors, if not supplied in "obj". |

`trees` |
List of trees, if not supplied in obj. |

`verbose` |
If > 0, print some information useful for debugging. |

There are four ways to compute inter-point dissimilarities from a treeClust object. If d.num = 1, two points differ by the number of trees in which they land in different leaves. "Mat" is required. If d.num = 2, the computation for d.num = 1 is used, but each tree gets a different weight. "Mat" and "tbl" are required.tbl" are required.

The computation for d.num = 3 requires that the set of trees be supplied. With this approach two observations differ, on a particular tree, according to how far apart they are on that tree. For d.num = 4, both tree and "tbl" are required; this is a weighted version of the d.num = 3 dissimilarity.

Object of class "dist" giving pairwise distances for the original data used to build the treeClust object.

Sam Buttrey

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