Albers S. (1996). Competitive online algorithms Tech. Rep. No. BRICS Lecture Series LS-96-2.

Amari S. (1998). Natural gradient works efficiently in learning Neural Comput. 10

Amari S, Park H, Fukumizu K. (2000). Adaptive method of realizing natural gradient learning for multilayer perceptrons. Neural computation. 12 [PubMed]

Barron AR. (1993). Universal approximation bounds for superposition of a sigmoidal function IEEE Trans Inform Theory. 39

Basak J. (2001). Learning Hough transform: a neural network model. Neural computation. 13 [PubMed]

Boz O. (2000). Converting a trained neural network to a decision tree DecText-decision tree extractor Unpublished doctoral dissertation (Available online at citeseer.ist.psu.edu-boz00converting.html).

Brodley CE, Utgoff PE. (1995). Multivariate decision trees Mach Learn. 19

Chen S, Chien J, Huang C. (2002). Compact decision trees with cluster validity for speech recognition IEEE Int. Conf. Acoustics, Speech, and Signal Processing.

Cho YH, Kim JK, Kim SH. (2002). A personalized recommender system based on web usage mining and decision tree induction Expert Systems With Applications. 23

Duda RO, Hart PE. (1973). Pattern Classification and Scene Analysis.

Duda RO, Hart PE, Stork DG. (2000). Pattern Classification (2nd edition).

Durkin J. (1992). Induction via ID3 AI Expert. 7

Fayyad UM, Irani KB. (1992). On the handling of continuous-values attributes in decision tree generation Mach Learn. 8

Frank E, Witten IH. (2000). Data mining.

Friedman JH. (1991). Multivariate Adaptive Regression Splines Ann Stat. 19

Friedman JH, Breiman L, Olshen RA, Stone CJ. (1983). Classification and regression trees.

Friedman JH, Kohavi R, Yun Y. (1996). Lazy decision trees Proceedings of the Thirteenth National Conference on Artificial Intelligence and the Eighth Innovative Applications of Artificial Intelligence Conference.

Garner S. (1995). Weka: The waikato environment for knowledge analysis Proc. of the New Zealand Computer Science Research Students Conference (Available online at citeseer.nj.nec.com-garner95weka.html).

Golea M, Marchand M. (1990). A growth algorithm for neural network decision trees Europhys Lett. 12

Haykin S. (1999). Neural Networks: A Comprehensive Foundation (2nd Ed).

Hohil ME, Liu D, Smith SH. (1999). Solving the N-bit parity problem using neural networks. Neural networks : the official journal of the International Neural Network Society. 12 [PubMed]

Jacobs RA, Jordan MI. (1993). Hierarchical mixtures of experts and the EM algorithm Tech. Rep. No. AI Memo 1440.

Jacobs RA, Jordan MI. (1994). Hierarchical mixtures of experts and the EM algorithm Neural Comput. 6

Jordan M. (1995). Why the logistic function? A tutorial discussion on probabilities and neural networks Available online at: http:--citeseer.nj.nec.com-jordan95why.html.

Kalai A, Vempala S. (nd). Efficient algorithms for online decision Available online at: http:--citeseer.nj.nec.com-585165.html.

Lavretsky E. (2000). On the exact solution of the Parity-N problem using ordered neural networks. Neural networks : the official journal of the International Neural Network Society. 13 [PubMed]

Lee SJ, Jone MT, Tsai HL. (1995). Construction of neural networks from decision trees J Inform Sci Eng. 11

Ljung L, Soderstrom T. (1986). Theory and practice of recursive identification.

Mao J, Jain A, Duin R. (2000). Statistical pattern recognition: A review IEEE Trans Pattern Anal Mach Intell. 22

Martin D. (nd). Hierarchical mixture of experts Available online at: http:--www.cs.berkeley.edu-dmartin-software-.

Mehta M, Rissanen J, Agrawal R. (1996). SLIQ: A fast scalable classifier for data mining Advances in database technology .

Merz CJ, Murphy PM. (1996). UCI repository of machine learning databases Tech Rep, University of California at Irvine.

Murphy K. (2001). The Bayes net toolbox for MATLAB Computing Science and Statistics. 33

Murphy K. (2003). Bayes net toolbox for MATLAB Available online at http:--www.ai.mit.edu-murphyk-Software-index.html.

Murthy SK, Kasif S, Salzberg S. (1994). A system for induction of oblique decision trees J Artif Intell Res. 2

Quinlan JR. (1993). C4.5: Programs for machine learning.

Quinlan JR. (1996). Improved use of continuous attributes in C4.5 J Art Intell. 4

Riley MD. (1989). Some applications of tree based modeling to speech and language indexing Proc. DARPA Speech and Natural Language Workshop.

Salzberg S, Delcher AL, Fasman KH, Henderson J. (1998). A decision tree system for finding genes in DNA. Journal of computational biology : a journal of computational molecular cell biology. 5 [PubMed]

Stromberg JE, Zrida J, Isaksson A. (1991). Neural trees-using neural nets in a tree classifier structure Proc. IEEE International Conference on Acoustics, Speech and Signal Processing.

Utgoff PE, Berkman NC, Clouse JA. (1997). Decision tree induction based on efficient tree restructuring Mach Learn. 29

Wu D, Bennett KP, Auslender L. (1998). On support vector decision trees for database marketing Tech. Rep. No. RPI Math Report 98-100.

Yang Y, Pedersen JO. (1997). A comparatative study on feature selection in text categorization Proc Fourteenth Int Conference On Machine Learning. ICML97

Zamir O, Etzioni O. (1998). Web document clustering: A feasibility demonstration Research and development in information retrieval.