148 related articles for article (PubMed ID: 18249768)
1. Extracting rules from trained neural networks.
Tsukimoto H
IEEE Trans Neural Netw; 2000; 11(2):377-89. PubMed ID: 18249768
[TBL] [Abstract][Full Text] [Related]
2. The functional localization of neural networks using genetic algorithms.
Tsukimoto H; Hatano H
Neural Netw; 2003 Jan; 16(1):55-67. PubMed ID: 12576106
[TBL] [Abstract][Full Text] [Related]
3. Extracting boolean and probabilistic rules from trained neural networks.
Liu P; Melkman AA; Akutsu T
Neural Netw; 2020 Jun; 126():300-311. PubMed ID: 32278262
[TBL] [Abstract][Full Text] [Related]
4. Extracting rules from neural networks as decision diagrams.
Chorowski J; Zurada JM
IEEE Trans Neural Netw; 2011 Dec; 22(12):2435-46. PubMed ID: 21335310
[TBL] [Abstract][Full Text] [Related]
5. Extracting M-of-N rules from trained neural networks.
Setiono R
IEEE Trans Neural Netw; 2000; 11(2):512-9. PubMed ID: 18249780
[TBL] [Abstract][Full Text] [Related]
6. Piecewise-linear neural networks and their relationship to rule extraction from data.
Holena M
Neural Comput; 2006 Nov; 18(11):2813-53. PubMed ID: 16999580
[TBL] [Abstract][Full Text] [Related]
7. Greedy rule generation from discrete data and its use in neural network rule extraction.
Odajima K; Hayashi Y; Tianxia G; Setiono R
Neural Netw; 2008 Sep; 21(7):1020-8. PubMed ID: 18442894
[TBL] [Abstract][Full Text] [Related]
8. Neural network explanation using inversion.
Saad EW; Wunsch DC
Neural Netw; 2007 Jan; 20(1):78-93. PubMed ID: 17029713
[TBL] [Abstract][Full Text] [Related]
9. Extraction of rules from artificial neural networks for nonlinear regression.
Setiono R; Leow WK; Zurada JM
IEEE Trans Neural Netw; 2002; 13(3):564-77. PubMed ID: 18244457
[TBL] [Abstract][Full Text] [Related]
10. A machine learning method for extracting symbolic knowledge from recurrent neural networks.
Vahed A; Omlin CW
Neural Comput; 2004 Jan; 16(1):59-71. PubMed ID: 15006023
[TBL] [Abstract][Full Text] [Related]
11. Extracting regression rules from neural networks.
Saito K; Nakano R
Neural Netw; 2002 Dec; 15(10):1279-88. PubMed ID: 12425443
[TBL] [Abstract][Full Text] [Related]
12. Recursive neural network rule extraction for data with mixed attributes.
Setiono R; Baesens B; Mues C
IEEE Trans Neural Netw; 2008 Feb; 19(2):299-307. PubMed ID: 18269960
[TBL] [Abstract][Full Text] [Related]
13. Sign-representation of Boolean functions using a small number of monomials.
Oztop E
Neural Netw; 2009 Sep; 22(7):938-48. PubMed ID: 19423284
[TBL] [Abstract][Full Text] [Related]
14. Novel maximum-margin training algorithms for supervised neural networks.
Ludwig O; Nunes U
IEEE Trans Neural Netw; 2010 Jun; 21(6):972-84. PubMed ID: 20409990
[TBL] [Abstract][Full Text] [Related]
15. Orthogonal search-based rule extraction (OSRE) for trained neural networks: a practical and efficient approach.
Etchells TA; Lisboa PJ
IEEE Trans Neural Netw; 2006 Mar; 17(2):374-84. PubMed ID: 16566465
[TBL] [Abstract][Full Text] [Related]
16. Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.
Akutsu T; Miyano S; Kuhara S
J Comput Biol; 2000; 7(3-4):331-43. PubMed ID: 11108466
[TBL] [Abstract][Full Text] [Related]
17. ANN-DT: an algorithm for extraction of decision trees from artificial neural networks.
Schmitz GJ; Aldrich C; Gouws FS
IEEE Trans Neural Netw; 1999; 10(6):1392-401. PubMed ID: 18252640
[TBL] [Abstract][Full Text] [Related]
18. Radical pruning: a method to construct skeleton radial basis function networks.
Augusteijn MF; Shaw KA
Int J Neural Syst; 2000 Apr; 10(2):143-54. PubMed ID: 10939346
[TBL] [Abstract][Full Text] [Related]
19. A study on rule extraction from several combined neural networks.
Bologna G
Int J Neural Syst; 2001 Jun; 11(3):247-55. PubMed ID: 11574962
[TBL] [Abstract][Full Text] [Related]
20. Neural subnet design by direct polynomial mapping.
Rohani K; Chen MS; Manry MT
IEEE Trans Neural Netw; 1992; 3(6):1024-6. PubMed ID: 18276501
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]