SELF-ORGANIZING NEURAL GROVE: EFFICIENT NEURAL NETWORK ENSEMBLES USING PRUNED SELF-GENERATIONG NEURAL TREES
J. Han and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers, San Francisco, CA, 2000.
L. Breiman, Bagging predictors, Machine Learning, (24) (1996), pp. 123-140.
R. E. Schapire, The strength of weak learnability, Machine Learning, (5) 2 (1990), pp. 197-227.
J. R. Quinlan, Bagging, Boosting, and C4.5, the Thirteenth National Conference on Artificial Intelligence, Portland, OR, (August 4-8, 1996), pp. 725-730.
G. Ratsch, T. Onoda, K. R. Muller, Soft margins for AdaBoost, Machine Learning, (42) 3 (2001), pp. 287-320.
S. Haykin, Neural Networks: A Comprehensive Foundation, second ed., Prentice-Hall, Upper Saddle River, NJ, 1999.
R. O. Duda, P. E. Hart, D. G. Stork, Pattern Classification, second ed., John Wiley & Sons Inc., New York, 2000.
W. X. Wen, A. Jennings, H. Liu, Learning a neural tree, the International Joint Conference on Neural Networks, Beijing, China, (November 3-6, 1992), Vol. 2, pp. 751-756.
T. Kohonen, Self-Organizing Maps, Springer, Berlin, 1995.
H. Inoue, H. Narihisa, Improving generalization ability of self-generating neural networks through ensemble averaging, in: T. Terano, H. Liu, A.L.P. Chen (Eds.), PAKDD 2000, Lecture Notes in Computer Science, Vol. 1805, Springer, Heidelberg, 2000, pp. 177-180.
H. Inoue, H. Narihisa, Optimizing a multiple classifier system, In: M. Ishizuka, A. Sattar (Eds.), PRICAI 2002, Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence), Vol. 2417, Springer, Heidelberg, 2002, pp. 285-294.
H. Inoue, K. Sugiyama, Self-organizing neural grove, the 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Berlin, Germany, (September 12-14, 2013), pp. 319-323.
M. Stone, Cross-validation: A review, Math. Operations for sch. Statist. Ser. Statistics, (9) 1 (1978), pp.127-139.
Y. Freund and R. E. Schapire, Boosting: Foundations and Algorithms, MIT Press, Cambridge, MA, 2012.
C.-C. Chang, C.-J. Lin, LIBSVM: A library for support vector machines, ACM Transactions on Intelligent Systems and Technology, (2) 27 (2011), pp. 1–27, software available at http://www.csie.ntu.edu.tw/cjlin/libsvm
C. Blake, C. Merz, UCI repository of machine learning databases, 1998. [Online]. Available: http://www.ics.uci.edu/mlearn/MLRepository. html
- There are currently no refbacks.