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Author: Przemyslaw Klesk

Affiliation: West Pomeranian University of Technology, Poland

Keyword(s): Statistical learning theory, Machine-learning, Vapnik-Chervonenkis dimension, Binary classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing ; Symbolic Systems

Abstract: We present an idea of probabilistic estimation of Vapnik-Chervonenkis dimension given a set of indicator functions. The idea is embedded in two algorithms we propose --- named A and A. Both algorithms are based on an approach that can be described as 'expand or divide and conquer'. Also, algorithms are parametrized by probabilistic constraints expressed in a form of (epsilon, delta)-precision. The precision implies how often and by how much the estimate can deviate from the true VC-dimension. Analysis of convergence and computational complexity for proposed algorithms is also presented.

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Paper citation in several formats:
Klesk, P. (2012). PROBABILISTIC ESTIMATION OF VAPNIK-CHERVONENKIS DIMENSION. In Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-95-9; ISSN 2184-433X, SciTePress, pages 262-270. DOI: 10.5220/0003721702620270

@conference{icaart12,
author={Przemyslaw Klesk},
title={PROBABILISTIC ESTIMATION OF VAPNIK-CHERVONENKIS DIMENSION},
booktitle={Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2012},
pages={262-270},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003721702620270},
isbn={978-989-8425-95-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - PROBABILISTIC ESTIMATION OF VAPNIK-CHERVONENKIS DIMENSION
SN - 978-989-8425-95-9
IS - 2184-433X
AU - Klesk, P.
PY - 2012
SP - 262
EP - 270
DO - 10.5220/0003721702620270
PB - SciTePress

- Science and Technology Publications, Lda.
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