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SplitWise Regression: Stepwise Modeling with Adaptive Dummy Encoding

Marcell T. Kurbucz, Nikolaos Tzivanakis, Nilufer Sari Aslam, Adam M. Sykulski

arXiv 21 May 2025 · Machine Learning

arXiv:2505.15423 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Capturing nonlinear relationships without sacrificing interpretability remains a persistent challenge in regression modeling. We introduce SplitWise, a novel framework that enhances stepwise regression. It adaptively transforms numeric predictors into threshold-based binary features using shallow decision trees, but only when such transformations improve model fit, as assessed by the Akaike Information Criterion (AIC) or Bayesian Information Criterion (BIC). This approach preserves the transparency of linear models while flexibly capturing nonlinear effects. Implemented as a user-friendly R package, SplitWise is evaluated on both synthetic and real-world datasets. The results show that it consistently produces more parsimonious and generalizable models than traditional stepwise and penalized regression techniques.

Citation extraction

33
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Raymaekers J, Rousseeuw PJ, Verdonck T, et al (2024) Fast linear model trees by pilot0.64422100%
2Henderson HV, Velleman PF (1981) Building multiple regression models interactively0.51121100%
3Therneau T, Atkinson B, Ripley B (2025) Recursive Partitioning and Regression Trees0.51121100%
4Akaike H (1974) A new look at the statistical model identification0.40511100%
5Breiman L, Friedman JH, Olshen RA, et al (1984) Classification and Regression Trees0.40511100%
6Breiman L (2001) Statistical modeling: The two cultures0.40511100%
7Caruana R, Lou Y, Gehrke J, et al (2015) Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission0.40511100%
8Doshi-Velez F, Kim B (2017) Towards a rigorous science of interpretable machine learning0.40511100%
9Efroymson MA (1960) Multiple regression analysis0.40511100%
10Fong Y, et al (2017) chngpt: threshold regression model estimation and inference0.40511100%

Showing the top 10 of 33 scored citations.