On data classification by iterative linear partitioning

DOI10.1016/j.dam.2004.04.003zbMath1099.68083OpenAlexW2046531788MaRDI QIDQ1885803

Martin Anthony

Publication date: 12 November 2004

Published in: Discrete Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.dam.2004.04.003

zbMATH Keywords

Pattern classificationDecision listsHyperplanesMulti-class classification

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (2)

Accurately learning from few examples with a polyhedral classifier ⋮ A mixed-integer programming approach to multi-class data classification problem

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Results on learnability and the Vapnik-Chervonenkis dimension
• A new polynomial-time algorithm for linear programming
• Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
• On defining sets of vertices of the hypercube by linear inequalities
• Dualization, decision lists and identification of monotone discrete functions
• Learning with discrete multivalued neurons
• A general lower bound on the number of examples needed for learning
• Partitioning points by parallel planes
• Learning with permutably homogeneous multiple-valued multiple-threshold perceptrons
• On specifying Boolean functions by labelled examples
• Discrete Mathematics of Neural Networks
• Learnability and the Vapnik-Chervonenkis dimension
• The capacity of multilevel threshold functions
• Computational limitations on learning from examples
• Estimating the efficiency of threshold representations of Boolean functions
• Using the Perceptron Algorithm to Find Consistent Hypotheses
• Structural risk minimization over data-dependent hierarchies
• Neural Network Learning
• Enumeration of Seven-Argument Threshold Functions
• Multisurface method of pattern separation
• On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
• Threshold Numbers and Threshold Completions

This page was built for publication: On data classification by iterative linear partitioning