Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

April 1, 1996, Vol. 8, No. 3, Pages 629-642
(doi: 10.1162/neco.1996.8.3.629)
© 1996 Massachusetts Institute of Technology
A Theoretical and Experimental Account of n-Tuple Classifier Performance
Article PDF (698.72 KB)
Abstract

The n-tuple recognition method is briefly reviewed, summarizing the main theoretical results. Large-scale experiments carried out on Stat-Log project datasets confirm this method as a viable competitor to more popular methods due to its speed, simplicity, and accuracy on the majority of a wide variety of classification problems. A further investigation into the failure of the method on certain datasets finds the problem to be largely due to a mismatch between the scales which describe generalization and data sparseness.