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Lecture Notes in Computer Science

Volumn 3578, Issue , 2005, Pages 220-227

An empirical study of hoeffding racing for model selection in k-nearest neighbor classification

(2) Yeh, Flora Yu Hui a Gallagher, Marcus a

a UNIVERSITY OF QUEENSLAND (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; LEARNING SYSTEMS; MATHEMATICAL MODELS; PARAMETER ESTIMATION;

DATASETS; MODEL SELECTION; RACING ALGORITHMS;

ALGORITHMS;

EID: 26444544167 PISSN: 03029743 EISSN: None Source Type: Conference Proceeding
DOI: 10.1007/11508069_29 Document Type: Conference Paper

Times cited : (4)

References (8)

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- O. Maron and A. W. Moore. Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation, in Advances in Neural Information Processing System, J.D. Cowan, Tesauro, G. Alspector, J., Editor. 1994, Morgan Kaufmann.
- (1994) Advances in Neural Information Processing System
- Maron, O.¹ Moore, A.W.²

2
- 0031069121
- The racing algorithm: Model selection for lazy learners
- O. Maron and A. W. Moore. The Racing Algorithm: Model Selection for Lazy Learners, in Artificial Intelligence Review. 1997. p. 193-225.
- (1997) Artificial Intelligence Review , pp. 193-225
- Maron, O.¹ Moore, A.W.²

3
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- A racing algorithm for configuring metaheuristics
- Morgan Kaufmann Publishers: New York, USA
- M. Birattari, T. Stuetzle, L. Paquete and K. Varrentrapp, A Racing Algorithm for Configuring Metaheuristics, in Genetic and Evolutionary Computation Conference 2002. 2002, Morgan Kaufmann Publishers: New York, USA. p. 11-18.
- (2002) Genetic and Evolutionary Computation Conference 2002 , pp. 11-18
- Birattari, M.¹ Stuetzle, T.² Paquete, L.³ Varrentrapp, K.⁴

4
- 35048885506
- Statistical racing techniques for improved empirical evaluation of evolutionary algorithms
- X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, H-P. schwefel, Editor, Springer: Birmingham, UK
- B. Yuan and M. Gallagher. Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms, in Parallel Problem Solving from Nature VIII, X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, H-P. schwefel, Editor. 2004, Springer: Birmingham, UK. p. 172-181.
- (2004) Parallel Problem Solving from Nature VIII , pp. 172-181
- Yuan, B.¹ Gallagher, M.²

5
- 0003684449
- The elements of statistical learning: Data mining, infererence and prediction
- Springer: New York, USA
- T. Hastie, R. Tibshirani and J.Friedman. The Elements of Statistical Learning: Data Mining, Infererence and Prediction, in Springer series in statistics. 2001, Springer: New York, USA.
- (2001) Springer Series in Statistics
- Hastie, T.¹ Tibshirani, R.² Friedman, J.³

6
- 0005631525
- Locally weighted learning
- C. G. Atkeson, A.W. Moore and S. Schaal. Locally Weighted Learning. Artificial Intelligence Review. Vol. 10. 1996.
- (1996) Artificial Intelligence Review , vol.10
- Atkeson, C.G.¹ Moore, A.W.² Schaal, S.³

7
- 0004255908
- New York, USA: The McGraw-Hill Companies, Inc.
- T. M. Mitchell. Machine Learning. 1997. New York, USA: The McGraw-Hill Companies, Inc.
- (1997) Machine Learning
- Mitchell, T.M.¹

8
- 0003408496
- University of California Irvine, USA
- S. Hittich, C. L. Blake and C. J. Merz, UCI Repository of Machine Learning Databases. 1998: University of California Irvine, USA. http://www.ics.uci.edu/~mlearn/MLRepository.html
- (1998) UCI Repository of Machine Learning Databases
- Hittich, S.¹ Blake, C.L.² Merz, C.J.³

* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.