On multivariate randomized classification trees: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si243.svg" display="inline" id="d1e4677"><mml:msub><mml:mrow><mml:mi>l</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>-based sparsity, VC dimension and decomposition methods-Reference-Cited by-同舟云学术

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On multivariate randomized classification trees: l0-based sparsity, VC dimension and decomposition methods

Published:2023-03 Issue: Volume:151 Page:106058
ISSN:0305-0548
Container-title:Computers & Operations Research
language:en
Short-container-title:Computers & Operations Research

Author:

Amaldi Edoardo^ORCID,Consolo Antonio,Manno Andrea^ORCID

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Modeling and Simulation,General Computer Science

Reference55 articles.

1. Learning optimal and fair decision trees for non-discriminative decision-making;Aghaei,2019

2. Learning optimal classification trees: Strong max-flow formulations;Aghaei,2020

3. Keel data-mining software tool: data set repository, integration of algorithms and experimental analysis framework;Alcalá-Fdez;J. Mult.-Valued Logic Soft Comput.,2011

4. Neural Network Learning: Theoretical Foundations;Anthony,2009

5. Computational Learning Theory;Anthony,1997

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Margin optimal classification trees;Computers & Operations Research;2024-01

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