Orthogonal decision trees

Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004

Volumn , Issue , 2004, Pages 427-430

  Kargupta, Hillol ^a,b   Dutta, Haimonti ^a  

^a Baltimore County   (United States)

^b AGNIK LLC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; EIGEN-ANALYSIS; FOURIER SPECTRA; REDUNDANCY-FREE ORTHOGONAL REPRESENTATION;

ALGORITHMS; COMPUTERIZED TOMOGRAPHY; DATA MINING; EIGENVALUES AND EIGENFUNCTIONS; FOURIER TRANSFORMS; LEARNING SYSTEMS; MATRIX ALGEBRA; SIGNAL PROCESSING;

TREES (MATHEMATICS);

EID: 19544371912     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2004.10072     Document Type: Conference Paper

References (9)

1. L. Breiman. Bagging predictors. Machine Learning, 24(2): 123-140, 1996.
2. L. Breiman. Random forests. Machine Learning, 45(1):5-32, 2001.
3. H. Drucker and C. Cortes. Boosting decision trees. Advances in Neural Information Processing Systems, 8:479-485, 1996.
4. H. Kargupta and B. Park. A fourier spectrum-based approach to represent decision trees for mining data streams in mobile environments. IEEE Transactions on Knowledge and Data Engineering, 16(2):216-229, 2002.
5. N. Linial, Y. Mansour, and N. Nisan. Constant depth circuits, fourier transform, and learnability. Journal of the ACM, 40:607-620, 1993.
6. B. H. Park and H. Kargupta. Constructing simpler decision trees from ensemble models using fourier analysis. In Proceedings of the 7th Workshop on Research Issues in Data Mining and Knowledge Discovery, ACM SIGMOD, pages 18-23, 2002.
7. J. R. Quinlan. Induction of decision trees. Machine Learning, 1(1):81-106, 1986.
8. W. N. Street and Y. Kim. A streaming ensemble algorithm (sea) for large-scale classificaiton. In Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, 2001.
9. D. Wolpert. Stacked generalization. Neural Networks, 5:241-259, 1992.