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Physarum Learner: a novel structure learning algorithm for Bayesian Networks inspired by Physarum polycephalum

Schön, Torsten (2013) Physarum Learner: a novel structure learning algorithm for Bayesian Networks inspired by Physarum polycephalum. PhD, Universität Regensburg.

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Date of publication of this fulltext: 12 Jul 2013 11:09

Abstract (English)

Two novel algorithms for learning Bayesian network structure from data based on the true slime mold Physarum polycephalum are introduced. The first algorithm called CPhyL calculates pairwise correlation coeffcients in the dataset. Within an initially fully connected Physarum-Maze, the length of the connections is given by the inverse correlation coeffcient between the connected nodes. Then, the ...

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Translation of the abstract (German)

In dieser Arbeit werden zwei neu entwickelte Strukturlernalgorithmen für Bayesische Netzwerke vorgestellt, welche von dem echten Schleimpilz Physarum polycephalum inspiriert sind. Der erste, C-PhyL genannte, Algorithmus berechnet paarweise Korrelationskoeffizienten in dem Datensatz. Ein Initial voll verbundenes Phyasarum-Maze wird generiert, in welchem die Distanzen zwischen den einzelnen Knoten ...

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Item type:Thesis of the University of Regensburg (PhD)
Date:12 July 2013
Referee:Prof. Dr. Elmar W. Lang
Date of exam:12 July 2013
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie
Keywords:Physarum Polycephalum, Bayesian Network, Structure Learning, C-Phyl, SO-Phyl
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
500 Science > 570 Life sciences
600 Technology > 610 Medical sciences Medicine
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:28415
Owner only: item control page

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