Citation Relationships

Basak J (2006) Online adaptive decision trees: pattern classification and function approximation. Neural Comput 18:2062-101 [PubMed]

References and models cited by this paper

References and models that cite this paper

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

Amari S (1967) Theory of adaptive pattern classifiers IEEE Trans 16:299-307

Amari S (1998) Natural gradient works efficiently in learning Neural Comput 10:251-276

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

Blake CL, Merz CJ (1998) UCI Repository of Machine Learning Databases

Boz O (2000) Converting a trained neural network to a decision tree DecText-decision tree extractor Unpublished doctoral dissertation (Available online at

Breiman L (1996) Bagging predictors Mach Learn 24:123-140

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

Brodley CE, Utgoff PE (1995) Multivariate decision trees Mach Learn 19:45-77

Broomhead DS, Lowe D (1988) Multivariable functional interpolation and adaptive networks Complex Systems 2:321-355

Buhmann MD (1990) Multivariate cardinal interpolation with radial basis functions Constructive Approximation 6:225-255

Burges CJC (1998) A tutorial on support vector machines for pattern recognition Data Mining And Knowledge Discovery 2:121-167

Canu S, Grandvalet Y, Rakotomamonjy A (2003) SVM and kernel methods matlab toolbox Available online at

Chien J, Huang C, Chen S (2002) Compact decision trees with cluster validity for speech recognition IEEE Int. Conf. Acoustics, Speech, and Signal Processing :873-876

Cho YH, Kim JK, Kim SH (2002) A personalized recommender system based on web usage mining and decision tree induction Expert Systems With Applications 23:329-342

Cristianini N, Shawe-taylor J (2000) Support vector machines Available online at

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

Durkin J (1992) Induction via ID3 AI Expert 7:48-53

Fayyad UM, Irani KB (1992) On the handling of continuous-values attributes in decision tree generation Mach Learn 8:87-102

Friedman J (2001) Greedy function approximation: A gradient boosting machine Ann Stat 29:1189-1232

Friedman JH (1991) Multivariate Adaptive Regression Splines Ann Stat 19:1-141

Friedman JH, Hastie T, Tibshirani R (1998) Additive logistic regression: A statistical view of boosting Tech Rep

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, Shrobe H:Senator T, ed. pp.717

Garner S (1995) Weka: The waikato environment for knowledge analysis Proc. of the New Zealand Computer Science Research Students Conference (Available online at :57-64

Geman D, Jedynak B (2001) Model-based classification trees IEEE Trans Information Theory 47:1075-1082

Girosi F, Jones M, Poggio T (1995) Regularization theory and neural network architectures Neural Comput 7:219-269

Golea M, Marchand M (1990) A growth algorithm for neural network decision trees Europhys Lett 12:105-110

Grimson WE (1982) A computational theory of visual surface interpolation. Philos Trans R Soc Lond B Biol Sci 298:395-427 [Journal] [PubMed]

Gunn SR (1998) Support vector machines for classification and regression Tech. Rep. No.

Guvenir HA, Uysal I (2000) Bilkent University function approximation repository Available online at

Harrison D, Rubinfeld D (1978) Hedonic prices and the demand for clean air J Environ Economics And Management 5:81-102

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

Horton P, Nakai K (1996) A probablistic classification system for predicting the cellular localization sites of proteins Intelligent Systems in Molecular Biology :109-115

Janikow CZ (1998) Fuzzy decision trees: issues and methods. IEEE Trans Syst Man Cybern B Cybern 28:1-14 [Journal] [PubMed]

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

Jordan MI, Jacobs RA (1994) Hierarchical mixtures of experts and the EM algorithm Neural Comput 6:181-214

Mehta M, Agrawal R, Rissanen J (1996) SLIQ: A fast scalable classifier for data mining Advances in database technology , Apers P:Bouzeghoub M:Gardarin G, ed. pp.18

Moody J, Darken C (1989) Fast learning in networks of locally-tuned processing units Neural Comput 1:281-294

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

Murphy K (2003) Bayes net toolbox for MATLAB Available online at

Murthy SK, Kasif S, Salzberg S (1994) A system for induction of oblique decision trees J Artif Intell Res 2:1-32

Nakai K, Kanehisa M (1991) Expert system for predicting protein localization sites in gram-negative bacteria. Proteins 11:95-110 [Journal] [PubMed]

Platt JC (1998) Sequential minimal optimization: a fast algorithm for training support vector machines Technical Report MSR-TR-98-14

Poggio T, Girosi F (1990) Regularization algorithms for learning that are equivalent to multilayer networks. Science 247:978-82 [Journal] [PubMed]

Poggio T, Girosi F (1990) Networks for approximation and learning Proc Of The IEEE 78:1481-1497

Powell MJD (1987) Radial basis functions for multivariable interpolation: A review Algorithms for approximation, Mason JC:Cox MG, ed.

Pyeatt LD, Howe AE (1998) Decision tree function approximation in reinforcement learning Tech. Rep. No. CS-98-112

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

Quinlan JR (1996) Improved use of continuous attributes in C4.5 J Art Intell 4:77-90

Riley MD (1989) Some applications of tree based modeling to speech and language indexing Proc. DARPA Speech and Natural Language Workshop :339-352

Schapire RE, Singer Y (1999) Improved boosting algorithms using confidence-rated predictions Mach Learn 37:297-336

Smola AJ, Scholkopf B (1998) On a kernel-based method for pattern recognition, regression, function approximation and operator inversion Algorithmica 22:211-231

Smola AJ, Scholkopf B (1998) A tutorial on support vector regression Tech. Rep. No. NC-TR-98-030

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 :137-140

Suarez A, Lutsko JF (1999) Globally optimal fuzzy decision trees for classification and regression IEEE Trans Pattern Analysis And Machine Intelligence 21:1297-1311

Tikhonov AN, Arsenin VY (1977) Solution of ill-posed problems

Utgoff PE, Berkman NC, Clouse JA (1997) Decision tree induction based on efficient tree restructuring Mach Learn 29:5-44

Uther WTB, Veloso MM (1998) Tree based discretization for continuous state space reinforcement learning Proc. Sixteenth National Conference on Artificial Intelligence (AAAI-98)

Vapnik V (1998) Statistical Learning Theory

Vapnik V, Golowich S, Smola A (1997) Support vector method for function approximation, regression estimation, and signal processing Advances in neural information processing systems, mozer M:Jordan M:Petsche T, ed. pp.281

Wang X, Dietterich T (1999) Efficient value function approximation using regression trees Proceedings Of The Ijcai-99 Workshop On Statistical Machine Learning For Large-scale Optimization, Dean T, ed.

Witten IH, Frank E (2000) Data mining

Yang Y, Pedersen JO (1997) A comparatative study on feature selection in text categorization Proc Fourteenth Int Conference On Machine Learning ICML97:412-420

Zamir O, Etzioni O (1998) Web document clustering: A feasibility demonstration Research and development in information retrieval :46-54

(64 refs)