A pivot-based simulated annealing algorithm to determine oblique splits for decision tree induction

DOI10.1007/s00180-022-01317-1MaRDI QIDQ6567426

Ferdinand Bollwein

Publication date: 5 July 2024

Published in: Computational Statistics (Search for Journal in Brave)

zbMATH Keywords

classificationsimulated annealingregressionoblique decision trees

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

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• A pivoting algorithm for convex hulls and vertex enumeration of arrangements and polyhedra
• HHCART: an oblique decision tree
• Oblique decision tree induction by cross-entropy optimization based on the von Mises-Fisher distribution
• Sparsity in optimal randomized classification trees
• The use of ranks to avoid the assumption of normality implicit in the analysis of variance.
• The generalized simplex method for minimizing a linear form under linear inequality restraints
• Optimal randomized classification trees
• A reflected feature space for CART
• Equation of State Calculations by Fast Computing Machines
• A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
• Handbook of metaheuristics
• Optimal classification trees

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