L-modified ILP evaluation functions for positive-only biological grammar learning

Mamer, T; Bryant, CH; McCall, JM

Abstract

We identify a shortcoming of a standard positive-only clause evaluation function within the context of learning biological grammars. To overcome this shortcoming we propose L-modification, a modification to this evaluation function such that the lengths of individual examples are considered. We use a set of bio-sequences known as neuropeptide precursor middles (NPP-middles). Using
L-modification to learn from these NPP-middles results in induced grammars that have a better performance than that achieved when using the standard positive-only clause evaluation function. We also show that L-modification improves the performance of induced grammars when learning on short, medium or long NPPs-middles. A potential disadvantage of L-modification is discussed. Finally, we show that, as the limit on the search space size increases, the greater is the increase in predictive performance arising from L-modification.

• Start Date: Sep 10, 2008
• End Date: Sep 12, 2008
• Publication Date: Jan 1, 2008
• Deposit Date: Feb 16, 2009
• Publicly Available Date: Feb 16, 2009
• Publisher: Springer
• Pages: 176-191
• Series Title: Lecture notes in artificial intelligence
• Series Number: 5194
• Book Title: Inductive logic programming
• ISBN: 9783540859277
• DOI: https://doi.org/10.1007/978-3-540-85928-4_16
• Keywords: inductive logic programming (ILP), biological grammar induction, machine learning, minimum description length (MDL)
• Publisher URL: http://dx.doi.org/10.1007/978-3-540-85928-4_16
• Additional Information: Paper originally presented at the 18th International Conference, ILP 2008 Prague, Czech Republic, September 10-12 2008