浅树聚类
Clustering with shallow trees
摘要：
我们提出了一种新的方法，层次聚类的基础上优化的成本函数在树的深度有限，我们推导出一个消息传递的方法，允许有效地解决它。该方法和算法可以被解释为两个众所周知的方法，即单链接和最近提出的亲和传播之间的自然插值。我们用这个一般方案分析了三个生物/医学结构化数据集（基于遗传信息的人口，基于序列和口头尸检的蛋白质），并表明插值技术提供了新的见解。
英文摘要：
We propose a new method for hierarchical clustering based on the optimisation of a cost function over trees of limited depth, and we derive a message--passing method that allows to solve it efficiently. The method and algorithm can be interpreted as a natural interpolation between two well-known approaches, namely single linkage and the recently presented Affinity Propagation. We analyze with this general scheme three biological/medical structured datasets (human population based on genetic information, proteins based on sequences and verbal autopsies) and show that the interpolation technique provides new insight.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
