Decision trees for functional variables

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2006, Pages 798-802

  Balakrishnan, Suhrid ^a   Madigan, David ^b  

^a RUTGERS UNIVERSITY   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FINANCIAL SETTING; FUNCTIONAL VARIABLES; INPUT VARIABLES;

BLOOD PRESSURE; CLASSIFICATION (OF INFORMATION); TWO DIMENSIONAL;

DECISION TREES;

EID: 84878092662     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2006.49     Document Type: Conference Paper

References (12)

1. A. Genkin, D. D. Lewis, and D. Madigan. Large-scale bayesian logisitic regression for text categorization., 2004. URL http://www.stat.rutgers.edu/ ~madigan/PAPERS/.
2. P. Geurts. Pattern extraction for time-series classification. In L. de Raedt and A. Siebes, editors, PKDD, LNAI 2168, pages 115 - 127, Freiburg, September 2001.
3. P. Geurts and L. Wehenkel. Segment and combine approach for non-parametric time-series classification. In PKDD, October 2005.
4. C. J. A. Gonzalez and J. J. R. Diez. Boosting intervalbased literals: Variable length and early classification. In A. Kandel M. Last and H. Bunke, editors, Data mining in time series databases. World Scientific, 2004.
5. S. Hettich and S. D. Bay. The UCI KDD archive, 1999. URL http://kdd.ics.uci.edu.
6. G. James and C. Sugar. Clustering for sparsely sampled functional data. Journal of the American Statistical Association, 98:397 - 408, 2003.
7. M. W. Kadous and C. Sammut. Classification of multivariate time series and structured data using constructive induction. Machine Learning Journal, 58:179 - 216, 2005.
8. M. Kudo, J. Toyama, and M. Shimbo. Multidimensional curve classification using passing-through regions. Pattern Recognition Letters, 20(11-13):1103 - 1111, 1999.
9. J. O. Ramsay and B. W. Silverman. Applied Functional Data Analysis: Methods and Case Studies. Springer-Verlag, New York, 2002.
10. N. Saito. Local feature extraction and its application using a library of bases. PhD thesis, Yale University, 1994.
11. H. Shimodaira, K. I. Noma, M. Nakai, and S. Sagayama. Dynamic time-alignment kernel in support vector machine. In NIPS, volume 2, pages 921 - 928, 2001.
12. Y. Yamada, E. Suzuki, H. Yokoi, and K. Takabayashi. Decision-tree induction from time-series data based on a standard-example split test. In ICML, pages 840-847, 2003.