On linear separability of data sets in feature space
By De-gang Chen, Qiang He, Xizhao Wang. 2007
31 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition
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In Artificial Intelligence
In Computational Theory and Mathematics
In Computer Vision and Pattern Recognition
Citations in the corpus
- On the Schoenberg Transformations in Data Analysis: Theory and Illustrations (2010, background): “On one hand, this result is completely expected: mapping the data into a high-dimensional feature space, in which the former become linearly separable, is a routine strategy in the Machine Learning community, developed ever since the nineties (see e.g. Chen et al. 2007 and references therein).”