The practical method of fractal dimensionality reduction based on Z-ordering technique

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

Volumn 4093 LNAI, Issue , 2006, Pages 542-549

  Yan, Guanghui ^a,b   Li, Zhanhuai ^a   Yuan, Liu ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b LANZHOU JIAOTONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; FEATURE EXTRACTION; LEARNING SYSTEMS; PATTERN RECOGNITION; SET THEORY; ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; FRACTAL DIMENSION; FRACTALS;

DATA SPACE; FEATURE SELECTION ALGORITHMS; FEATURE SUBSET; FRACTAL DIMENSIONALITY REDUCTION (FDR); BETTER PERFORMANCE; FEATURE SELECTION ALGORITHM; FEATURE SETS; FRACTAL DIMENSIONALITY; HIGH-DIMENSIONAL DATA SPACE; MULTIPLE SCANNING; PRACTICAL METHOD;

FRACTALS; DATA MINING;

EID: 33749373566     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11811305_60     Document Type: Conference Paper

References (18)

1. R Baeza-Yates, G Navarro. Block-addressing indices for approximate text retrieval. In: Forouzan Golshani, Kia Makki. (Eds.): Proc of the 6th Int'l Conf on Information and Knowledge Management. New York: ACM Press (1997) 1-8
2. R Agrawal, C Faloutsos, A Swamil. Efficient similarity search in sequence databases1 In: David B Lomet. (Eds.): Proc of the 4th Int'l Conf Foundations of Data Organization and Algorithms. Berlin : Springer-Verlag (1993) 69-84
3. Daxin Jiang, Chun Tang, Aidong Zhang. Cluster Analysis for Gene Expression Data: A Survey. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING Vol. 16, No. 11. (2004) 1370-1386
4. M.D. Schena, R. Shalon, R. Davis, P. Brown. Quantitative Monitoring of Gene Expression Patterns with a Compolementatry DNA Microarray. Science, vol. 270. (1995) 467-470
5. R. Bellman. Adaptive Control Process:A Guide Tour. Princeton University Press, Princeton, New Jersey (1961)
6. H. Vafaie and K. A. D. Jong. Robust Feature Selection Algorithms. In Intl. Conf. on Tools with AI, Boston, MA (1993) 356-363
7. D. W. Aha, R. L. Bankert. A Comparative Evaluation of Sequential Feature Selection Algorithms. In Artificial Intelligence and Statistics V, Springer-Verlag, New York, New York (1996) 199-206
8. M. Scherf, W. Brauer. Feature Selection by Means of a Feature Weighting Approach. Technical Report FKI-221-97, Technische Universität München, Munich (1997)
9. A.Blum, P.Langley. Selection of Relevant Features and Examples in Machine Learning. AI, vol. 97. (1997) 245-271.
10. Camastra Francesco. Data dimensionality estimation methods: a survey. Pattern Recognition, vol. 36. (2003) 2945-2954.
11. P.Langley, S. Sage. Scaling to Domains with many Irrelevant Features. In R.Greiner (eds.): Computational learning theory and natural learning systems, vol. 4, Cambridge, MA: MIT Press (1997)
12. C.Faloutsos, B.Seeger, A. J. M. Traina, C. Traina, Jr. Spatial Join Selectivity Using Power Laws. In ACM SIGMOD, Dallas, TX, (2000) 177-188
13. I.Kamel,C. Faloutsos. Hubert R-tree: An Improved R-tree using Fractals. In 20th VLDB, Chile (1994) 500-509
14. D.Chakraborty, A. Ashir, T. Suganuma G., Mansfield Keeni, T. K. Roy,N. Shiratori. Self-similar and fractal nature of Internet traffic. INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, vol. 14. (2004) 119-129
15. Caetano Traina Jr., Agma Traina, et al. Fast feature selection using fractal dimension. In XV Brazilian DB Symposium, João Pessoa-PA-Brazil, (2000) 158-171
16. Yubin Bao., Ge Yu., Huanliang Sun., Daling Wang. Performance Optimization of Fractal Dimension Based Feature Selection Algorithm. In:Q. Li, G. Wang, and L. Feng. (Eds.): WAIM 2004, LNCS, Vol. 3129. Springer-Verlag Berlin Heidelberg (2004) 739-744
17. Ls Liebovitch, T.Toth. A Fast Algorithm to Determine Fractal Dimensions by Box Counting[J]. Physics Letters, Vol.141A(8). (1989) 386-390
18. J.Orenstein, T.H.Merrett. A class of data structures for associative searching. In Proceedings of the Third ACM SIGACT- SIGMOD Symposium on Principles of Database Systems (1984) 181-190