Publikationsansicht

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis (2009)

Abstract
We study the problem of domain transfer for a supervised classification task in mRNA splicing. We consider a number of recent domain transfer methods from machine learning, including some that are novel, and evaluate them on genomic sequence data from model organisms of varying evolutionary distance. We find that in cases where the organisms are not closely related, the use of domain adap- tation methods can help improve classification performance.

Details der Publikation
Download http://eprints.pascal-network.org/archive/00004350/
Archiv PASCAL EPrints (United Kingdom)
Keywords Computational, Information-Theoretic Learning with Statistics, Learning/Statistics & Optimisation, Brain Computer Interfaces, Theory & Algorithms
Typ Conference or Workshop Item, PeerReviewed
Verknüpfungen http://eprints.pascal-network.org/archive/00004350/01/NIPS2008-Schweikert_5401[0].pdf