A clustering-based discretization for supervised learning

DOI10.1016/j.spl.2010.01.015zbMath1186.62087OpenAlexW2026846567MaRDI QIDQ968468

B. E. Eshmatov

Publication date: 5 May 2010

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://surface.syr.edu/eecs/3

zbMATH Keywords

discretizationclusteringsupervised learningbinning

Mathematics Subject Classification ID

Related Items (4)

Prediction of overdispersed count data using real-time cluster-based discretization of explanatory variables ⋮ Unsupervised discretization by two-dimensional MDL-based histogram ⋮ Fuzzy partitioning of continuous attributes through discretization methods to construct fuzzy decision tree classifiers ⋮ Lattice structure based metric for feature data fusion

Uses Software

• C4.5

Cites Work

• Global discretization of continuous attributes as preprocessing for machine learning
• Modeling by shortest data description
• Very simple classification rules perform well on most commonly used datasets
• Squeezing the last drop: Cluster-based classification algorithm

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