A note on split selection bias in classification trees

DOI10.1016/S0167-9473(03)00064-1zbMath1429.62264OpenAlexW2162154995WikidataQ85633944 ScholiaQ85633944MaRDI QIDQ956844

B. E. Eshmatov

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(03)00064-1

zbMATH Keywords

Pearson chi-square statisticKolmogorov-Smirnov statistic\(P\)-valueCramér \(V^{2}\) statistic

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items

Variable selection for functional density trees ⋮ Item-focussed trees for the identification of items in differential item functioning ⋮ Regression trees for longitudinal and multiresponse data ⋮ Generalised indirect classifiers ⋮ Unbiased variable importance for random forests ⋮ Tree-structured modelling of varying coefficients ⋮ Three Steps Strategy to Search for Optimum Classification Trees ⋮ Rasch trees: a new method for detecting differential item functioning in the Rasch model ⋮ Maximally selected chi-squared statistics and non-monotonic associations: an exact approach based on two cutpoints ⋮ Unbiased split selection for classification trees based on the Gini index ⋮ Tree-structured scale effects in binary and ordinal regression ⋮ Empirical characterization of random forest variable importance measures

Uses Software

• C4.5
• bootstrap

Cites Work

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• Multiple comparisons in induction algorithms
• Percentage points of a weighted Kolmogorov-Smirnov statistic
• Maximally Selected Chi Square Statistics
• Minimally Selected P and Other Tests for A Single Abrupt Changepoint in A Binary Sequence