title: The use of classification trees for bioinformatics.
abstract: Classification trees are non-parametric 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.
authors.affiliation: Yale University in China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Chen
authors.forename: Minghui
authors.initials: M
authors.lastname: Wang
authors.forename: Heping
authors.initials: H
authors.lastname: Zhang