Median topographic maps for biomedical data sets
Clausthal University of Technology（克劳斯塔尔工业大学）；INRIA Rocquencourt（法国国家信息与自动化研究所罗克库尔中心）
英文摘要：
Median clustering extends popular neural data analysis methods such as the self-organizing map or neural gas to general data structures given by a dissimilarity matrix only. This offers flexible and robust global data inspection methods which are particularly suited for a variety of data as occurs in biomedical domains. In this chapter, we give an overview about median clustering and its properties and extensions, with a particular focus on efficient implementations adapted to large scale data analysis.
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。
