SIRUS: stable and interpretable RUle set for classification

DOI10.1214/20-EJS1792zbMath1458.62126arXiv1908.06852OpenAlexW3110802511MaRDI QIDQ2219234

Clément Bénard, Erwan Scornet, Gérard Biau, Sébastien Da Veiga

Publication date: 19 January 2021

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.06852

zbMATH Keywords

rulesclassificationstabilityinterpretabilityrandom forests

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)

Related Items (3)

Mathematical optimization in classification and regression trees ⋮ Consistent regression using data-dependent coverings ⋮ sirus

Uses Software

• UCI-ml
• CRAN
• DLMF
• rpart
• RWeka
• C50
• randomForest
• C4.5
• ENDER
• ranger
• pre
• FOIL
• nodeHarvest
• arulesCBA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Predictive learning via rule ensembles
• Bagging predictors
• Learning Certifiably Optimal Rule Lists for Categorical Data
• Stability
• Node harvest
• Open-source machine learning: R meets Weka
• Interpretable classifiers using rules and Bayesian analysis: building a better stroke prediction model
• A finite sample distribution-free performance bound for local discrimination rules
• Statistical modeling: The two cultures. (With comments and a rejoinder).
• Stable feature selection for biomarker discovery
• Rejoinder on: ``A random forest guided tour
• Comparing the Characteristics of Gene Expression Profiles Derived by Univariate and Multivariate Classification Methods
• Distribution-free inequalities for the deleted and holdout error estimates
• 10.1162/153244302760200704
• Definitions, methods, and applications in interpretable machine learning
• Beyond Sequential Covering – Boosted Decision Rules
• Asymptotic expansions of the hypergeometric function with two large parameters—application to the partition function of a lattice gas in a field of traps
• Abundance‐Based Similarity Indices and Their Estimation When There Are Unseen Species in Samples
• A Class of Statistics with Asymptotically Normal Distribution
• The elements of statistical learning. Data mining, inference, and prediction
• Random forests

This page was built for publication: SIRUS: stable and interpretable RUle set for classification