An unbiased method for constructing multilabel classification trees
type: Item
instance of: scholarly article
title: An unbiased method for constructing multilabel classification trees
zbMATH Open document ID: 1429.62260
author: B. E. Eshmatov
published in: Computational Statistics and Data Analysis
publication date: 2008-11-26T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 5374046
zbMATH Keywords: multilabel classification tree
zbMATH Keywords: bias in variable selection
zbMATH Keywords: power in variable selection
zbMATH Keywords: stopping rule
zbMATH Keywords: pruning
describes a project that uses: C4.5
describes a project that uses: BoosTexter
MaRDI profile type: Publication
full work available at URL: j.csda.2003.10.009
OpenAlex ID: W2055150205
cites work: Q3327527
cites work: Modelling multivariate binary data with alternating logistic regressions
cites work: A likelihood-based method for analysing longitudinal binary responses
cites work: Regression Models for a Bivariate Discrete and Continuous Outcome with Clustering
cites work: Multivariate generalizations of the Wald-Wolfowitz and Smirnov two-sample tests
cites work: Graph-theoretic measures of multivariate association and prediction
cites work: Marginal Regression Models for Clustered Ordinal Measurements
cites work: Q4365875
cites work: Tree-Structured Classification Via Generalized Discriminant Analysis
cites work: Testing the equality of distributions of random vectors with categorical components.
cites work: Improved boosting algorithms using confidence-rated predictions
cites work: BoosTexter: A boosting-based system for text categorization
cites work: Multivariate data analysis and modeling through classification and regression trees
cites work: Classification Trees for Multiple Binary Responses
DOI: 10.1016/J.CSDA.2003.10.009
description: scientific article; zbMATH DE number 5374046