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# Table 2 Description of common agglomerative metrics used as cluster merging criteria

Agglomerative Methods | ||
---|---|---|

Abbreviation | Full Name | Description |

single | Single Linkage | Merge those clusters for which the minimum distance between their elements is the least one. |

complete | Complete Linkage | Merge those clusters for which the maximum distance between their elements is the least one. |

average | Average Linkage | Merge those clusters for which the mean distance between their elements is the least one. |

centroid | Centroid Method | Merge those clusters for which the (squared) Euclidean distance between their centroids or means is the least one. |

median | Median Method | Merge those clusters for which the Euclidean distance between their weighted centroids is the least one; called median because the centre of each new cluster is based on the combination of the centroids of the merged groups. |

ward | Ward's Criterion, or else Ward's Minimum-Variance Method | Merge those clusters for which the increase in variance for the resulting group is the least one. |

EML | EML | Merge those clusters that maximize the likelihood at each level of the resulted hierarchy; similar to Ward's method but removes the bias toward equal-sized clusters. |

density | Density Linkage | Merge those clusters for which the probability density estimate for the resulting group is maximized; consists of two steps: 1. the dissimilarity measure is based on reciprocals of the estimates of the density midway between the members of each cluster within a defined area or otherwise is infinite, 2. a single linkage cluster analysis follows. (Examples of different types of density methods are the kth-nearest-neighbor, the uniform kernel and the Wong's hybrid ones which among others differ with respect to the neighbourhood within which the density is measured) |

mcquitty | McQuitty's Similarity Analysis | Merge those clusters for which the average of their distances, or else the distance of the resulting group, from the remaining ones is minimal. |