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→Agglomerative clustering example 凝聚聚类实例
* The maximum distance between elements of each cluster (also called [[complete-linkage clustering]]):
* The maximum distance between elements of each cluster (also called [[complete-linkage clustering]]):
*每个簇元素之间的最大距离（又名[[完全链路集]])
::<math> \max \{\, d(x,y) : x \in \mathcal{A},\, y \in \mathcal{B}\,\}. </math>
::<math> \max \{\, d(x,y) : x \in \mathcal{A},\, y \in \mathcal{B}\,\}. </math>
* The minimum distance between elements of each cluster (also called [[single-linkage clustering]]):
* The minimum distance between elements of each cluster (also called [[single-linkage clustering]]):
*每个簇的元素之间的最小距离（也称为[[单个链路集]]):
::<math> \min \{\, d(x,y) : x \in \mathcal{A},\, y \in \mathcal{B} \,\}. </math>
::<math> \min \{\, d(x,y) : x \in \mathcal{A},\, y \in \mathcal{B} \,\}. </math>
* The mean distance between elements of each cluster (also called average linkage clustering, used e.g. in [[UPGMA]]):
* The mean distance between elements of each cluster (also called average linkage clustering, used e.g. in [[UPGMA]]):
*每个簇元素之间的平均距离（也称为平均链路集）：
::<math> {1 \over {|\mathcal{A}|\cdot|\mathcal{B}|}}\sum_{x \in \mathcal{A}}\sum_{ y \in \mathcal{B}} d(x,y). </math>
::<math> {1 \over {|\mathcal{A}|\cdot|\mathcal{B}|}}\sum_{x \in \mathcal{A}}\sum_{ y \in \mathcal{B}} d(x,y). </math>
* The sum of all intra-cluster variance.
* The sum of all intra-cluster variance.
*所有簇内方差之和。
* The increase in variance for the cluster being merged ([[Ward's method]]<ref name="wards method"/>)
* The increase in variance for the cluster being merged ([[Ward's method]]<ref name="wards method"/>)
*合并的聚类的方差增加([[离差平方和法]]<ref name="离差平方和法"/>)。
* The probability that candidate clusters spawn from the same distribution function (V-linkage).
* The probability that candidate clusters spawn from the same distribution function (V-linkage).
*候选集群从相同的分布函数中产生的概率（V—链路）。
人们总是可以决定停止群集时，有一个足够少的群集(数目标准)。有些联系还可能保证集群之间的距离大于以前的集群，然后当集群之间的距离太远而无法合并时就可以停止集群(距离标准)。然而，这不是例如，质心链接的情况下，所谓的逆转(反转，偏离超节拍)可能发生的情况。
人们总是可以决定停止群集时，有一个足够少的群集(数目标准)。有些联系还可能保证集群之间的距离大于以前的集群，然后当集群之间的距离太远而无法合并时就可以停止集群(距离标准)。然而，这不是例如，质心链接的情况下，所谓的逆转(反转，偏离超节拍)可能发生的情况。
== Divisive clustering分裂聚类 ==
== Divisive clustering分裂聚类 ==