A distributed framework for trimmed Kernel k-Means clustering
نویسندگان
چکیده
منابع مشابه
A distributed framework for trimmed Kernel k-Means clustering
Data clustering is an unsupervised learning task that has found many applications in various scientific fields. The goal is to find subgroups of closely related data samples (clusters) in a set of unlabeled data. Kernel k-Means is a state of the art clustering algorithm. However, in contrast to clustering algorithms that can work using only a limited percentage of the data at a time, Kernel k-M...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2015
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2015.02.020