Automated design of multiple-class piecewise linear classifiers

DOI10.1007/BF01908599zbMath0698.62061MaRDI QIDQ912541

Jack Sklansky, Youngtae Park

Publication date: 1989

Published in: Journal of Classification (Search for Journal in Brave)

zbMATH Keywords

clusterhyperplaneslinksprototypecutting of straight line segments joining pairs of opposed pointsk-nearest neighbor rulemultiple-class piecewise linear classifiersnear- Bayes-optimal decision surfacesupporting theoremtraining-set consistencywindow training

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Pattern recognition, speech recognition (68T10)

Related Items (8)

Non-parametric classifier-independent feature selection ⋮ GEOMETRIC PROXIMITY GRAPHS FOR IMPROVING NEAREST NEIGHBOR METHODS IN INSTANCE-BASED LEARNING AND DATA MINING ⋮ Alternating multiconlitron: a novel framework for piecewise linear classification ⋮ An incremental piecewise linear classifier based on polyhedral conic separation ⋮ A novel piecewise linear classifier based on polyhedral conic and max-min separabilities ⋮ A simple and fast multi-class piecewise linear pattern classifier ⋮ Classification through incremental max-min separability ⋮ Unnamed Item

Cites Work

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• A learning procedure for multisurface method of pattern separation
• Locally Trained Piecewise Linear Classifiers
• Stochastic models for closed boundary analysis: Representation and reconstruction
• Finding Prototypes For Nearest Neighbor Classifiers
• Two Modifications of CNN
• Asymptotic Properties of Nearest Neighbor Rules Using Edited Data
• Nearest neighbor pattern classification
• Multisurface method of pattern separation

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