Abstract
Dimensionality Reduction algorithms have wide precedent for use in preprocessing for classification problems. This paper presents a new algorithm, based on a modification to Stochastic Neighbour Embedding and t-Distributed SNE to use the Laplacian distribution instead of, respectively, the Gaussian Distribution and a mismatched pair of the Gaussian Distribution and Student’s t-Distribution. Experimental results are presented to demonstrate that this modification yields improvement.
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Cook, L.V., Gao, J. (2010). Dimensionality Reduction for Classification through Visualisation Using L1SNE. In: Li, J. (eds) AI 2010: Advances in Artificial Intelligence. AI 2010. Lecture Notes in Computer Science(), vol 6464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17432-2_21
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DOI: https://doi.org/10.1007/978-3-642-17432-2_21
Publisher Name: Springer, Berlin, Heidelberg
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