On Perfect Clustering of High Dimension, Low Sample Size Data
نویسندگان
چکیده
منابع مشابه
Clustering High Dimension, Low Sample Size Data Using the Maximal Data Piling Distance
We propose a new hierarchical clustering method for high dimension, low sample size (HDLSS) data. The method utilizes the fact that each individual data vector accounts for exactly one dimension in the subspace generated by HDLSS data. The linkage that is used for measuring the distance between clusters is the orthogonal distance between affine subspaces generated by each cluster. The ideal imp...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2020
ISSN: 0162-8828,2160-9292,1939-3539
DOI: 10.1109/tpami.2019.2912599