Discovering patterns in EEG-Signals: Comparative study of a few methods

Miroslav Kubat, Doris Flotzinger, Gert Pfurtscheller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

The objective of this paper is to draw the attention of the ML-researchers to the domain of data analysis. The issue is illustrated by an attractive case study—automatic classification of non-averaged EEG-signals. We applied several approaches and obtained best results from a combination of an ID3-like program with Bayesian learning.

Original languageEnglish (US)
Title of host publicationMachine Learning
Subtitle of host publicationECML 1993 - European Conference on Machine Learning, Proceedings
EditorsPavel B. Brazdil
PublisherSpringer Verlag
Pages366-371
Number of pages6
ISBN (Print)9783540566021
DOIs
StatePublished - Jan 1 1993
Externally publishedYes
Event1st European Conference on Machine Learning, ECML 1993 - Vienna, Austria
Duration: Apr 5 1993Apr 7 1993

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume667 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st European Conference on Machine Learning, ECML 1993
CountryAustria
CityVienna
Period4/5/934/7/93

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kubat, M., Flotzinger, D., & Pfurtscheller, G. (1993). Discovering patterns in EEG-Signals: Comparative study of a few methods. In P. B. Brazdil (Ed.), Machine Learning: ECML 1993 - European Conference on Machine Learning, Proceedings (pp. 366-371). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 667 LNAI). Springer Verlag. https://doi.org/10.1007/3-540-56602-3_152