title: Mouse chromosome classification by radial basis function network with fast orthogonal search.
abstract: This paper provides the results of our study on automatic classification of mouse chromosomes. A radial basis function neural network was compared with a multi-layer perceptron and a probabilistic neural network. The networks were trained and tested with 3723 chromosomes presented to each network as 30-point banding profiles. The radial basis function classifier trained with the fast orthogonal search learning rule provided the best unconstrained classification error rate of 12.7% which was obtained with a training set of 2250 chromosomes.
authors.affiliation: Department of Electrical and Computer Engineering, University of Maine, Orono, USA
authors.forename: M T.
authors.initials: MT
authors.lastname: Musavi
authors.forename: R J.
authors.initials: RJ
authors.lastname: Bryant
authors.forename: M
authors.initials: M
authors.lastname: Qiao
authors.forename: M T.
authors.initials: MT
authors.lastname: Davisson
authors.forename: E C.
authors.initials: EC
authors.lastname: Akeson
authors.forename: B D.
authors.initials: BD
authors.lastname: French