Stability-Based Model Selection

NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Volumn , Issue , 2002, Pages 617-624

  Lange, Tilman ^a   Braun, Mikio L ^a   Roth, Volker ^a   Buhmann, Joachim M ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

ASSESSMENT SCHEME; CROSS VALIDATION; LEARNING TASKS; MODEL ASSESSMENT; MODEL SELECTION; MODELING PARAMETERS; SEMI-SUPERVISED; SPECIFIC LEARNING; STABILITY MEASURE; UPPER BOUND;

STABILITY;

EID: 85156245319     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. A. A. Alizadeh et al. Distinct types of diffuse large b-cell lymphoma identified by gene expression profiling. Nature, 403:503-511, 2000.
2. M. Bittner et al. Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature, 406(3):536-540, 2000.
3. O. Bousquet and A. Elisseeff. Stability and generalization. Journal of Machine Learning Research, 2:499-526, 2002.
4. J. Breckenridge. Replicating cluster analysis: Method, consistency and validity. Multivariate Behavioural research, 1989.
5. B. Fischer, T. Zöller, and J. M. Buhmann. Path based pairwise data clustering with application to texture segmentation. In LNCS Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer Verlag, 2001.
6. J. Fridlyand and S. Dudoit. Applications of resampling methods to estimate the number of clusters and to improve the accuracy of a clustering method. Technical Report 600, Statistics Department, UC Berkeley, September 2001.
7. T.R. Golub et al. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science, pages 531-537, October 1999.
8. T. Hofmann and J. M. Buhmann. Pairwise data clustering by deterministic annealing. IEEE PAMI, 19(1), January 1997.
9. A. K. Jain and R. C. Dubes. Algorithms for Clustering Data. Prentice-Hall, Inc., 1988.
10. Michael J. Kearns and Dana Ron. Algorithmic stability and sanity-check bounds for leave-one-out cross-validation. In Computational Learing Theory, pages 152-162, 1997.
11. H.W. Kuhn. The hungarian method for the assignment problem. Naval Res. Logist. Quart., 2:83-97, 1955.
12. K. Rose, E. Gurewitz, and G. C. Fox. A deterministic annealing approach to clustering. Pattern Recognition Letters, 11(9):589-594, 1990.
13. R. Tibshirani, G. Walther, D. Botstein, and P. Brown. Cluster validation by prediction strength. Technical report, Statistics Department, Stanford University, September 2001.
14. R. Tibshirani, G. Walther, and T. Hastie. Estimating the number of clusters via the gap statistic. Technical report, Statistics Department, Stanford University, March 2000.