Learning data discretization via convex optimization

DOI10.1007/s10994-017-5654-4zbMath1457.68231OpenAlexW2735875562MaRDI QIDQ1707483

Michal Sofka, Karel Bartos, Ondrej Fikar, Vojtěch Franc

Publication date: 3 April 2018

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

Full work available at URL: https://doi.org/10.1007/s10994-017-5654-4

zbMATH Keywords

classificationconvex optimizationhistogramsparameter discretizationpiecewise constant embeddingpiecewise linear embedding

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Convex programming (90C25) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• UCI-ml
• MODL

Cites Work

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• MODL: a Bayes optimal discretization method for continuous attributes
• Discretization for Naive-Bayes learning: managing discretization bias and variance
• On the handling of continuous-valued attributes in decision tree generation
• Data mining and data visualization
• General and efficient multisplitting of numerical attributes
• Decoding by Linear Programming
• Stable signal recovery from incomplete and inaccurate measurements
• Compressed sensing

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