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Extracting Propositional Rules from Feed-forward Neural Networks — A New Decompositional Approach Sebastian Bader and Steffen H¨olldobler and Valentin Mayer-Eichberger International Center for Computational Logic Tech
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Document Date: 2006-11-03 20:49:32

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Berlin / Pittsburgh / /

Company

Oxford University Press / Neural Networks / /

Currency

pence / /

Facility

Carnegie Mellon University / /

IndustryTerm

given network / search trees / coalition search tree / search technique / suitable search tree / left-depth-first search / layered feedforward network / modified search tree / bipolar sigmoidal networks / search tree / feed-forward network / given feed-forward network / search space / extraction algorithm / learning algorithms / done using a suitable search tree / /

Organization

German Research Foundation / Carnegie Mellon University / H¨olldobler and Valentin Mayer-Eichberger International Center for Computational Logic Technische Universit¨at Dresden / Oxford University / Computer Science Department / /

Person

Krysia Broda / Artur S. d’Avila Garcez / Jude W. Shavlik / Dov M. Gabbay / John W. Lloyd / Joachim Diederich / Geoffrey G. Towell / Robert Andrews / Christopher M. Bishop / Sebastian Bader / Raul Rojas / Mostefa Golea / /

Position

Bishop / feed-forward / /

Product

Algorithm 3 / /

ProvinceOrState

Pennsylvania / /

PublishedMedium

Machine Learning / /

Technology

COMBO algorithm / Applying Algorithm / neural network / PA using Algorithm / modified algorithm / COOP algorithm / caching / Machine Learning / 5 Return F. Algorithm / extraction algorithm / /

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