Conditional validity of inductive conformal predictors

DOI10.1007/s10994-013-5355-6zbMath1273.68307arXiv1209.2673OpenAlexW2166693382WikidataQ62046668 ScholiaQ62046668MaRDI QIDQ374136

Vladimir Vovk

Publication date: 22 October 2013

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1209.2673

zbMATH Keywords

boostingROC curvesMARTbatch mode of learningconditional validityinductive conformal predictorsspam detection

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (9)

Conditional predictive inference for stable algorithms ⋮ Classification with minimum ambiguity under distribution heterogeneity ⋮ Training-conditional coverage for distribution-free predictive inference ⋮ Unnamed Item ⋮ Unsupervised streaming anomaly detection for instrumented infrastructure ⋮ Distribution-Free Predictive Inference For Regression ⋮ Least Ambiguous Set-Valued Classifiers With Bounded Error Levels ⋮ Conformal prediction: a unified review of theory and new challenges ⋮ Valid Model-Free Prediction of Future Insurance Claims

Uses Software

• UCI-ml
• DAAG
• DLMF
• AdaBoost.MH
• ElemStatLearn
• DAAGxtras

Cites Work

• Greedy function approximation: A gradient boosting machine.
• A decision-theoretic generalization of on-line learning and an application to boosting
• Distribution-Free Prediction Sets
• Distribution-free Prediction Bands for Non-parametric Regression
• Non-Parametric Estimation II. Statistically Equivalent Blocks and Tolerance Regions--The Continuous Case
• Nonparametric Estimation, III. Statistically Equivalent Blocks and Multivariate Tolerance Regions--The Discontinuous Case
• Nonparametric Estimation IV
• Non-Parametric Estimation. I. Validation of Order Statistics
• Introduction to nonparametric estimation
• Stochastic gradient boosting.
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