Cohen S, Dror G, Ruppin E. (2007). Feature selection via coalitional game theory. Neural computation. 19 [PubMed]

See more from authors: Cohen S · Dror G · Ruppin E

References and models cited by this paper

Alon U et al. (1999). Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proceedings of the National Academy of Sciences of the United States of America. 96 [PubMed]

Bengtsson H. (2003). The R.oo package object-oriented programming with references using standard R code Proc 3rd Intl Workshop on Distributed Statistical Computing.

Billera LJ, Heath D, Raanan J. (1978). Internal telephone billing rates a novel application of non-atomic game theory Operations Res. 26

Blake CL, Merz CJ. (1998). UCI Repository of Machine Learning Databases.

Blum AL, Langley P. (1997). Selection of relevant feature and examples in machine learning Art Intell. 97

Breiman L. (2001). Random forests Mach Learn. 45

Dreyfus G, Dubois R, Oussar Y, Stoppiglia H. (2003). Ranking a random feature for variable and feature selection J Mach Learn Res. 3

Gefeller O, Land M, Eide GE. (1998). Averaging attributable fractions in the multifactorial situation: assumptions and interpretation. Journal of clinical epidemiology. 51 [PubMed]

Gillick L, Cox S. (1989). Some statistical issues in the comparison of speech recognition algorithms ICASSP. 1

Guyon I. (2003). Design of experiments for the NIPS 2003 variable selection benchmark Tutorial at the NIPS 2003 Workshop on Feature Extraction and Feature selection.

Guyon I, Elisseeff A. (2003). An introduction to variable and feature selection J Mach Learn Res. 3

Joachims T. (1999). Making large-scale SVM learning practical Advances in kernel methods-Support vector learning.

Kanji G. (1994). 100 statistical tests.

Keinan A, Sandbank B, Hilgetag CC, Meilijson I, Ruppin E. (2004). Fair attribution of functional contribution in artificial and biological networks. Neural computation. 16 [PubMed]

Keinan A, Sandbank B, Hilgetag CC, Meilijson I, Ruppin E. (2006). Axiomatic scalable neurocontroller analysis via the Shapley value. Artificial life. 12 [PubMed]

Kohavi R, John GH. (1996). Wrappers for feature subset selection Artificial Intelligence. 97

Koller D, Sahami M. (1996). Toward optimal feature selection Proc 13th Intl Conf Mach Learn.

Kushmerick N. (1999). Learning to remove Internet advertisements Proc 3rd Intl Conf Autonomous Agents.

Papadimitriou CH, Feigenbaum J, Shenker S. (2001). Sharing the cost of multicast transmissions J Comput System Sci. 63

Personnaz L, Rivals I. (2003). MLPs (mono-layer polynomials and multi-layer perceptrons) for nonlinear modeling J Mach Learn Res. 3

Poggio T et al. (2001). Feature selection for SVMs Advances in neural information processing systems. 13

Reuter Reuters. (1997). Reuters collection Distribution for research purposes by David Lewis. Available online at http:--www.daviddlewis.com-resources-testcollections-reuters21578-.

Roth AE. (1979). Axiomatic models of bargaining.

Shapley LS. (1953). A value for n-person games Contributions To The Theory Of Games. 2

Shapley LS, Shubik M. (1954). A method for evaluating the distribution of power in a committee system Am Politic Sci Rev. 48

Shubik M. (1962). Incentives, decentralized control, the assignment of joint costs and internal pricing Management Sci. 8

Shubik M. (1985). Game theory in the social sciences.

Theiler J, Perkins S, Lacker K. (2003). Grafting: Fast, incremental feature selection by gradient descent in function space J Mach Learn Res. 3

Vapnik V, Guyon I, Weston J, Barnhill S. (2002). Gene selection for cancer classification using support vector machines Mach Learn. 46

References and models that cite this paper
This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.