Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms-Reference-Cited by-同舟云学术

Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms

Published:2024-01-31 Issue:3 Volume:38 Page:1364-1416
ISSN:1384-5810
Container-title:Data Mining and Knowledge Discovery
language:en
Short-container-title:Data Min Knowl Disc

Author:

Gomes Mantovani Rafael,Horváth Tomáš,Rossi André L. D.,Cerri Ricardo,Barbon Junior Sylvio,Vanschoren Joaquin,Carvalho André C. P. L. F. de

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Talent Management in Autonomous Vehicle Control Technologies -- The Project is supported by the Hungarian Government and cofinanced by the European Social Fund

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10618-024-01002-5.pdf

Reference106 articles.

1. Abe S (2005) Support vector machines for pattern classification. Springer, London

2. Alcobaça E, Siqueira F, Rivolli A et al (2020) MFE: towards reproducible meta-feature extraction. J Mach Learn Res 21:111:1-111:5

3. Ali S, Smith-Miles KA (2006) A meta-learning approach to automatic kernel selection for support vector machines. Neurocomputing 70(13):173–186

4. Andradottir S (2015) A review of random search methods. In: Fu MC (ed) Handbook of simulation optimization, international series in operations research & management science, vol 216. Springer, New York, pp 277–292

5. Bache K, Lichman M (2013) UCI machine learning repository. http://archive.ics.uci.edu/ml

Cited by 5 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. Decarbonization strategies in the maritime industry: An analysis of dual-fuel engine performance and the carbon intensity indicator;Renewable and Sustainable Energy Reviews;2024-08

2. The Prediction of Pectin Viscosity Using Machine Learning Based on Physical Characteristics—Case Study: Aglupectin HS-MR;Sustainability;2024-07-10

3. Customer Purchase Prediction Using Optimized Decision Tree with Particle Swarm Optimization;2024 International Conference on Data Science and Its Applications (ICoDSA);2024-07-10

4. Assessing the knot in a noose position by thyrohyoid and cervical spine fracture patterns in suicidal hangings using machine learning algorithms: A new insight into old dilemmas;Forensic Science International;2024-04

5. Efficiency of Identification of Blackcurrant Powders Using Classifier Ensembles;Foods;2024-02-24