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

Neural Computation

February 1, 2000, Vol. 12, No. 2, Pages 293-304
(doi: 10.1162/089976600300015790)
© 2000 Massachusetts Institute of Technology
N-tuple Network, CART, and Bagging
Article PDF (151.08 KB)
Abstract

Similarities between bootstrap aggregation (bagging) and N-tuple sampling are explored to propose a retina-free data-driven version of the N-tuple network, whose close analogies to aggregated regression trees, such as classification and regression trees (CART), lead to further architectural enhancements. Performance of the proposed algorithms is compared with the traditional versions of the N-tuple and CART networks on a number of regression problems. The architecture significantly outperforms conventional N-tuple networks while leading to more compact solutions and avoiding certain implementational pitfalls of the latter.