Parsimonious Side Propagation
| dc.contributor.author | Mangasarian, O.L. | |
| dc.contributor.author | Bradley, P.S. | |
| dc.date.accessioned | 2013-06-21T21:29:05Z | |
| dc.date.available | 2013-06-21T21:29:05Z | |
| dc.date.issued | 1997 | |
| dc.description.abstract | A fast parsimonious linear-programming-based algorithm for training neural networks is proposed that suppresses redundant features while using a minimal number of hidden units. This is achieved by propagating sideways to newly added hidden units the task of separating successive groups of unclassified points. Computational results how improvement o 26.53% and 19.76? in tenfold cross-validation test correctness over a parsimonious perceptron on two publicly available datasets. | en |
| dc.identifier.citation | 97-11 | en |
| dc.identifier.uri | http://digital.library.wisc.edu/1793/66051 | |
| dc.title | Parsimonious Side Propagation | en |
| dc.type | Technical Report | en |