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Authors: T. Schön 1 ; M. Stetter 2 ; A. M. Tomé 3 and E. W. Lang 4

Affiliations: 1 University of Regensburg and University of Applied Science Weihenstephan-Triesdorf, Germany ; 2 University of Applied Science Weihenstephan-Triesdorf, Germany ; 3 University of Aveiro and University of Regensburg, Portugal ; 4 University of Regensburg, Germany

ISBN: 978-989-8565-36-5

Keyword(s): Bayesian Network, Structure Learning, Physarum Solver, LAGD Hill Climber.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics ; Sensor Networks ; Soft Computing

Abstract: A novel structure learning algorithm for Bayesian Networks based on a Physarum Learner is presented. The length of the connections within an initially fully connected Physarum-Maze is taken as the inverse Pearson correlation coefficient between the connected nodes. The Physarum Learner then estimates the shortest indirect paths between each pair of nodes. In each iteration, a score of the surviving edges is incremented. Finally, the highest scored connections are combined to form a Bayesian Network. The novel Physarum Learner method is evaluated with different configurations and compared to the LAGD Hill Climber showing comparable performance with respect to quality of training results and increased time efficiency for large data sets.

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Paper citation in several formats:
Schön, T.; Stetter, M.; M. Tomé, A. and W. Lang, E. (2013). A New Physarum Learner for Network Structure Learning from Biomedical Data.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 151-156. DOI: 10.5220/0004227401510156

@conference{biosignals13,
author={T. Schön. and M. Stetter. and A. M. Tomé. and E. W. Lang.},
title={A New Physarum Learner for Network Structure Learning from Biomedical Data},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={151-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004227401510156},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - A New Physarum Learner for Network Structure Learning from Biomedical Data
SN - 978-989-8565-36-5
AU - Schön, T.
AU - Stetter, M.
AU - M. Tomé, A.
AU - W. Lang, E.
PY - 2013
SP - 151
EP - 156
DO - 10.5220/0004227401510156

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