loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Author: Przemysław Klęsk

Affiliation: Westpomeranian University of Technology, Poland

ISBN: 978-989-8425-40-9

Keyword(s): Statistical learning theory, Bounds on generalization, Cross-validation, Empirical risk minimization, Structural risk minimization, Vapnik–Chervonenkis dimension.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems ; Uncertainty in AI

Abstract: Typically, the n-fold cross-validation is used both to: (1) estimate the generalization properties of a model of fixed complexity, (2) choose from a family of models of different complexities, the one with the best complexity, given a data set of certain size. Obviously, it is a time-consuming procedure. A different approach — the Structural Risk Minimization is based on generalization bounds of learning machines given by Vapnik (Vapnik, 1995a; Vapnik, 1995b). Roughly speaking, SRM is O(n) times faster than n-fold cross-validation but less accurate. We state and prove theorems, which show the probabilistic relationship between the two approaches. In particular, we show what e-difference between the two, one may expect without actually performing the crossvalidation. We conclude the paper with results of experiments confronting the probabilistic bounds we derived.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.212.93.234

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Klęsk P. (2011). A RELATIONSHIP BETWEEN CROSS-VALIDATION AND VAPNIK BOUNDS ON GENERALIZATION OF LEARNING MACHINES.In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 5-17. DOI: 10.5220/0003121000050017

@conference{icaart11,
author={Przemysław Klęsk},
title={A RELATIONSHIP BETWEEN CROSS-VALIDATION AND VAPNIK BOUNDS ON GENERALIZATION OF LEARNING MACHINES},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={5-17},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003121000050017},
isbn={978-989-8425-40-9},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - A RELATIONSHIP BETWEEN CROSS-VALIDATION AND VAPNIK BOUNDS ON GENERALIZATION OF LEARNING MACHINES
SN - 978-989-8425-40-9
AU - Klęsk P.
PY - 2011
SP - 5
EP - 17
DO - 10.5220/0003121000050017

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.