Brush is a new symbolic regression method that integrates tree-like rules with function optimization, matching or beating decision trees and forests on clinical scoring tasks while producing simpler interpretable models.
2004Hybrid geneticalgorithm foroptimization problems with permutation property.Computers & Operations Research31, 2453–2471
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
MAMO uses multi-agent RL to automatically select reward weights for constrained optimization problems in non-stationary environments.
citing papers explorer
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Towards symbolic regression for interpretable clinical decision scores
Brush is a new symbolic regression method that integrates tree-like rules with function optimization, matching or beating decision trees and forests on clinical scoring tasks while producing simpler interpretable models.
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A Multi-Agent system for Multi-Objective constrained optimization
MAMO uses multi-agent RL to automatically select reward weights for constrained optimization problems in non-stationary environments.