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Subspace Learning Machine (SLM): Methodology and Performance. (arXiv:2205.05296v1 [cs.LG])
May 12, 2022, 1:11 a.m. | Hongyu Fu, Yijing Yang, Vinod K. Mishra, C.-C. Jay Kuo
cs.LG updates on arXiv.org arxiv.org
Inspired by the feedforward multilayer perceptron (FF-MLP), decision tree
(DT) and extreme learning machine (ELM), a new classification model, called the
subspace learning machine (SLM), is proposed in this work. SLM first identifies
a discriminant subspace, $S^0$, by examining the discriminant power of each
input feature. Then, it uses probabilistic projections of features in $S^0$ to
yield 1D subspaces and finds the optimal partition for each of them. This is
equivalent to partitioning $S^0$ with hyperplanes. A criterion is developed …
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