Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences
نویسندگان
چکیده
منابع مشابه
Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences
We present a systematic approach to the mathematical treatment of the t-distributed stochastic neighbor embedding (t-SNE) and the stochastic neighbor embedding (SNE) method. This allows an easy adaptation of the methods or exchange of their respective modules. In particular, the divergence which measures the difference between probability distributions in the original and the embedding space ca...
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Stochastic neighbor embedding (SNE) is a method of dimensionality reduction (DR) that involves softmax similarities measured between all pairs of data points. In order to build a low-dimensional embedding, SNE tries to reproduce the similarities observed in the highdimensional data space. The capability of softmax similarities to fight the phenomenon of norm concentration has been studied in pr...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2012
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2012.02.034