Parametric nonlinear dimensionality reduction using kernel t-SNE
نویسندگان
چکیده
منابع مشابه
Parametric nonlinear dimensionality reduction using kernel t-SNE
Novel non-parametric dimensionality reduction techniques such as t-distributed stochastic neighbor embedding (t-SNE) lead to a powerful and flexible visualization of high-dimensional data. One drawback of non-parametric techniques is their lack of an explicit out-of-sample extension. In this contribution, we propose an efficient extension of t-SNE to a parametric framework, kernel t-SNE, which ...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2015
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2013.11.045