Handling numeric attributes in hoeffding trees

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5012 LNAI, Issue , 2008, Pages 296-307

  Pfahringer, Bernhard ^a   Holmes, Geoffrey ^a   Kirkby, Richard ^a  

^a UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; CLASSIFICATION (OF INFORMATION); GAUSSIAN DISTRIBUTION; LEARNING ALGORITHMS; LEARNING SYSTEMS;

BEST SPLIT POINTS; HOEFFDING TREES; LEARNING CLASSIFICATION ALGORITHMS;

TREES (MATHEMATICS);

EID: 44649179894     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68125-0_27     Document Type: Conference Paper

References (16)

1. Agrawal, R., Imielinski, T., Swami, A.: Database mining: A performance perspective. IEEE Transactions on Knowledge and Data Engineering 5(6), 914-925 (1993)
2. Agrawal, R., Swami, A.: A one-pass space-efficient algorithm for finding quantiles. In: International Conference on Management of Data (1995)
3. Alsabti, K., Ranka, S., Singh, V.: A one-pass algorithm for accurately estimating quantiles for disk-resident data. In: International Conference on Very Large Databases, pp. 346-355 (1997)
4. Chan, T.F., Lewis, J.G.: Computing standard deviations: Accuracy. Communications of the ACM 22(9), 526-531 (1979)
5. Domingos, P., Hulten, G.: Mining high-speed data streams. In: International Conference on Knowledge Discovery and Data Mining, pp. 71-80 (2000)
6. Gama, J., Medas, P., Rocha, R.: Forest trees for on-line data. In: ACM Symposium on Applied Computing, pp. 632-636 (2004)
7. Gama, J., Rocha, R., Medas, P.: Accurate decision trees for mining high-speed data streams. In: International Conference on Knowledge Discovery and Data Mining, pp. 523-528 (2003)
8. Greenwald, M., Khanna, S.: Space-efficient online computation of quantile summaries. In: ACM Special Interest Group on Management Of Data Conference, pp. 58-66 (2001)
9. Holmes, G., Kirkby, R., Pfahringer, B.: Stress-testing hoeffding trees. In: European Conference on Principles and Practice of Knowledge Discovery in Databases, pp. 495-502 (2005)
10. Hulten, G., Domingos, P.: VFML - a toolkit for mining high-speed time-changing data streams (2003), http://www.cs.Washington.edu/dm/vfml/
11. 2 algorithm for dynamic calculation of quantiles and histograms without storing observations. Communications of the ACM 28(10), 1076-1085 (1985)
12. Manku, G.S., Rajagopalan, S., Lindsay, B.G.: Approximate medians and other quantiles in one pass and with limited memory. In: ACM Special Interest Group on Management Of Data Conference, pp. 426-435 (1998)
13. Munro, J.I., Paterson, M.: Selection and sorting with limited storage. Theoretical Computer Science 12, 315-323 (1980)
14. Ross Quinlan, J.: Improved use of continuous attributes in C4. Journal of Artificial Intelligence Research 4, 77-90 (1996)
15. Vitter, J.S.: Random sampling with a reservoir. ACM Transactions on Mathematical Software 11(1), 37-57 (1985)
16. Welford, B.P.: Note on a method for calculating corrected sums of squares and products. Technometrics 4(3), 419-420 (1962)