Premium
The use of classification trees for bioinformatics
Author(s) -
Chen Xiang,
Wang Minghui,
Zhang Heping
Publication year - 2011
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.14
Subject(s) - interpretability , feature selection , machine learning , computer science , artificial intelligence , selection (genetic algorithm) , decision tree , feature (linguistics) , data mining , tree (set theory) , bioinformatics , data science , biology , mathematics , mathematical analysis , philosophy , linguistics
Classification trees are nonparametric statistical learning methods that incorporate feature selection and interactions, possess intuitive interpretability, are efficient, and have high prediction accuracy when used in ensembles. This paper provides a brief introduction to the classification tree‐based methods, a review of the recent developments, and a survey of the applications in bioinformatics and statistical genetics. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 55‐63 DOI: 10.1002/widm.14 This article is categorized under: Algorithmic Development > Hierarchies and Trees Algorithmic Development > Statistics Technologies > Classification Technologies > Machine Learning