Improved graph-based SFA: information preservation complements the slowness principle
نویسندگان
چکیده
منابع مشابه
Improved graph-based SFA: Information preservation complements the slowness principle
Slow feature analysis (SFA) is an unsupervised-learning algorithm that extracts slowly varying features from a multi-dimensional time series. A supervised extension to SFA for classification and regression is graph-based SFA (GSFA). GSFA is based on the preservation of similarities, which are specified by a graph structure derived from the labels. It has been shown that hierarchical GSFA (HGSFA...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2019
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-019-05860-9