Abstract
Sign random projections (SRP) transform multi-dimensional vector into a binary string storing only the sign of the random projection values. Previous works showed that the obtained binary strings can be used to estimate the angle between vectors which can be used to speed up the nearest neighbors search. In this paper, we investigate their application to classification problem. We introduce an SRP classifier which works on these binary strings. The training procedure of this new classifier is very simple, yet producing correct classification result with high probability if the two classes are linearly separable.
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Marukatat, S. (2014). Classification with Sign Random Projections. In: Pham, DN., Park, SB. (eds) PRICAI 2014: Trends in Artificial Intelligence. PRICAI 2014. Lecture Notes in Computer Science(), vol 8862. Springer, Cham. https://doi.org/10.1007/978-3-319-13560-1_56
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DOI: https://doi.org/10.1007/978-3-319-13560-1_56
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13559-5
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