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Joint Optimization of Piecewise Linear Ensembles
May 2, 2024, 4:42 a.m. | Matt Raymond, Angela Violi, Clayton Scott
cs.LG updates on arXiv.org arxiv.org
Abstract: Tree ensembles achieve state-of-the-art performance despite being greedily optimized. Global refinement (GR) reduces greediness by jointly and globally optimizing all constant leaves. We propose Joint Optimization of Piecewise Linear ENsembles (JOPLEN), a piecewise-linear extension of GR. Compared to GR, JOPLEN improves model flexibility and can apply common penalties, including sparsity-promoting matrix norms and subspace-norms, to nonlinear prediction. We evaluate the Frobenius norm, $\ell_{2,1}$ norm, and Laplacian regularization for 146 regression and classification datasets; JOPLEN, combined …
abstract apply art arxiv cs.lg extension flexibility global linear optimization performance state tree type
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