A bias-variance analysis of state-of-the-art random forest text classifiers

DOI10.1007/s11634-020-00409-4OpenAlexW3043513630MaRDI QIDQ2036167

Leonardo Rocha, Thiago Salles, Marcos A. Gonçalves

Publication date: 28 June 2021

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-020-00409-4

zbMATH Keywords

random foreststext classificationbias variance analysis

Mathematics Subject Classification ID

Robust parameter designs (62K25) Parametric inference and fuzziness (62F86)

Uses Software

• GeneSrF
• VADER
• obliqueRF

Cites Work

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• Variance and bias for general loss functions
• Bounds on the Bayes classification error based on pairwise risk functions
• Extremely randomized trees
• Random forests

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