Semi-supervised fuzzy c-means clustering of biological data

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

Volumn 3849 LNAI, Issue , 2006, Pages 259-266

  Ceccarelli, M ^a   Maratea, A ^a  

^a UNIVERSITY OF SANNIO   (Italy)

Author keywords

Adaptive Metric; Fuzzy Clustering; Semi Supervised Learning; Validity Index

Indexed keywords

CONSTRAINT THEORY; DATA ACQUISITION; ENTROPY; LEARNING SYSTEMS;

ADAPTIVE METRIC; FUZZY CLUSTERING; SEMI-SUPERVISED LEARNING; VALIDITY INDEX;

FUZZY SETS;

EID: 33745157484     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11676935_32     Document Type: Conference Paper

References (16)

1. Bar-Hillel A., Hertz T., Shental N. and Weinshall D.(2005) "Learning a Mahalanobis Metric from Equivalence Constraints", Journal of Machine Learning Research, vol.6, pp. 937-965.
2. Bezdek J. C. (1981) Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, NY.
3. Bilenko M., Basu S., Mooney R.J. (2004) "Integrating Constraints and Metric Learning in Semi-Supervised Clustering", Proceedings of the 21st ICML, pp. 81-88.
4. Chang H. and Yeung D.Y. (2004) "Locally Linear Metric Adaptation for Semi-Supervised Clustering", Proceedings of the 21st ICML, pp. 153-160.
5. R.J.Cho, M.J.Campbell, E.A.Winzeler, L.Steinmetz, A.Conway, L.Wodicka, T.G.Wolfsberg, A.E.Gabrielian, D.Landsman, D.J.Lockhart, R.W.Davis (1998)"A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle", Molecular Cell, vol. 2, pp. 65-73.
6. S.Chu, J. DeRisi, M.Eisen, J. Mulholland, D.Botstein, P.O. Brown, I.Herskowitz (1998) "The Transcriptional Program of Sporulation in Budding Yeast", Science, vol. 282, pp.699-705.
7. De Bie T., Momma M., Cristianini N. (2003) "Efficiently Learning the Metric With Side-Information", Lecture Notes in Artificial Intelligence, vol. 2842, pp.175-189.
8. Dembl D.,Kastner P. (2003) "Fuzzy C-means Method for Clustering Microarray Data", Bioinformatics, vol. 19, pp. 973-980.
9. M.B.Eisen, P.T.Spellman, P.O.Brown, D.Botstein (1998) "Cluster Analysis and Display of Genome-Wide Expression Patterns", PNAS vol. 95, pp. 14863-14868.
10. T.R. Golub, D.K. Slonim, P.Tamayo, C.Huard, M.Gaasenbeek, J.P. Mesirov, H.Coller, M.L.Loh, J.R. Downing, M.A.Caligiuri, C.D.Bloomfield, E.S.Lander (1999) "Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring", Science, vol. 286, pp.531-537.
11. Kirkpatrick S., C.D. Gelatt Jr and M.P. Vecchi (1983),"Optimization by Simulated Annealing", Science, vol. 220, pp. 671- 680.
12. Shental N., Bar-Hillel A., Hertz T. and Weinshall D.(2003) "Computing Gaussian Mixture Models with EM using Equivalence Constraints", Proceedings of Neural Information Processing Systems 2003, vol.16.
13. Schultz M. and Joachims T. (2003) "Learning a Distance Metric From Relative Comparisons", Proceedings of Neural Information Processing Systems 2003, vol. 16.
14. P.T.Spellman, G.Sherlock, M.Q.Zhang, V.R.Iyer, K.Anders, M.B.Eisen, P.O.Brown, D.Botstein, B. Futcher (1998) "Comprehensive Identification of Cell Cycle-Regulated Genes of the Yeast Saccaromyces Cervesiae by Microarray Hybridization" Molecular Biology of the Cell, vol. 9, pp. 3273-3297.
15. Xing E. P., Ng A. Y., Jordan M. I., Russell S. (2002) "Distance Metric Learning, With Application to Clustering With Side-Information", Advances in Neural Information Processing Systems, vol. 15.
16. Zhengdong L., Leen T. (2004) "Semi-supervised Learning with Penalized Probabilistic Clustering" Proceedings of Neural Information Processing Systems 2004, vol. 17.