[[1] R. E. Schapire, The strength of weak learn-ability, Mach. Learn., vol. 5, no. 2, pp. 197–227, Jul. 1990. [Online]. Available: http://dx.doi.org/10.1023/A:102264880076010.1023/A:1022648800760]Open DOISearch in Google Scholar
[[2] D. H. Wolpert, Stacked generalization, Neural Networks, vol. 5, pp. 241–259, 199210.1016/S0893-6080(05)80023-1]Search in Google Scholar
[[3] J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, On combining classifiers, IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 3, pp. 226–239, Mar. 1998. [Online]. Available: http://dx.doi.org/10.1109/34.66788110.1109/34.667881]Open DOISearch in Google Scholar
[[4] P. Bachman, O. Alsharif, and D. Precup, Learning with pseudo-ensembles, in Advances in Neural Information Processing Systems 27, Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, and K. Weinberger, Eds. Curran Associates, Inc., 2014, pp. 3365–3373]Search in Google Scholar
[[5] A. Strehl and J. Ghosh, Cluster Ensembles – A Knowledge Reuse Framework for Combining Multiple Partitions, Journal on Machine Learning Research (JMLR), vol. 3, pp. 583–617, Dec. 2002]Search in Google Scholar
[[6] J. da Silva and M. Klusch, Inference on distributed data clustering, in Machine Learning and Data Mining in Pattern Recognition, ser. Lecture Notes in Computer Science, P. Perner and A. Imiya, Eds. Springer Berlin Heidelberg, 2005, vol. 3587, pp. 610–619. [Online]. Available: http://dx.doi.org/10.1007/11510888_6010.1007/11510888_60]Open DOISearch in Google Scholar
[[7] W. Pedrycz, Collaborative fuzzy clustering, Pattern Recognition Letters, vol. 23, no. 14, pp. 1675–1686, 200210.1016/S0167-8655(02)00130-7]Search in Google Scholar
[[8] N. Grozavu, M. Ghassany, and Y. Bennani, Learning confidence exchange in collaborative clustering, in IJCNN, 2011, pp. 872–87910.1109/IJCNN.2011.6033313]Search in Google Scholar
[[9] W. Pedrycz and K. Hirota, A consensus-driven fuzzy clustering, Pattern Recogn. Lett., vol. 29, no. 9, pp. 1333–1343, 200810.1016/j.patrec.2008.02.015]Search in Google Scholar
[[10] N. Grozavu, G. Cabanes, and Y. Bennani, Diversity analysis in collaborative clustering, in IEEE World Congress on Computational Intelligence, 201410.1109/IJCNN.2014.6889528]Search in Google Scholar
[[11] B. Depaire, R. Falcón, K. Vanhoof, and G. Wets, Pso driven collaborative clustering: A clustering algorithm for ubiquitous environments, Intell. Data Anal., vol. 15, no. 1, pp. 49–68, Jan. 2011. [Online]. Available: http://dl.acm.org/citation.cfm?id=1937721.193772510.3233/IDA-2010-0455]Search in Google Scholar
[[12] M. Ghassany, N. Grozavu, and Y. Bennani, Collaborative clustering using prototype-based techniques, International Journal of Computational Intelligence and Applications, vol. 11, no. 03, p. 1250017, 201210.1142/S1469026812500174]Search in Google Scholar
[[13] S. Zhang, C. Zhang, and X. Wu, Knowledge Discovery in Multiple Databases, ser. Advanced Information and Knowledge Processing. Springer, 2004. [Online]. Available: http://dx.doi.org/10.1007/978-0-85729-388-610.1007/978-0-85729-388-6]Open DOISearch in Google Scholar
[[14] W. Pedrycz, Interpretation of clusters in the framework of shadowed sets, Pattern Recogn. Lett., vol. 26, no. 15, pp. 2439–2449, 200510.1016/j.patrec.2005.05.001]Search in Google Scholar
[[15] N. Grozavu and Y. Bennani, Topological collaborative clustering, Australian Journal of Intelligent Information Processing Systems, vol. 12, no. 3, 2010]Search in Google Scholar
[[16] M. Ghassany, N. Grozavu, and Y. Bennani, Collaborative clustering using prototype-based techniques, International Journal of Computational Intelligence and Applications, vol. 11, no. 3, 201210.1142/S1469026812500174]Search in Google Scholar
[[17] N. Grozavu and Y. Bennani, Topological Collaborative Clustering, in LNCS Springer of ICONIP’10 : 17th International Conference on Neural Information Processing, 2010]Search in Google Scholar
[[18] T. Kohonen, Self-organized formation of topologically correct feature maps, Biol. Cyb., vol. 43, pp. 59–69, 198210.1007/BF00337288]Search in Google Scholar
[[19] Analysis of a simple self-organizing process, Biol. Cyb., vol. 44, pp. 135–140, 198210.1007/BF00317973]Search in Google Scholar
[[20] C. M. Bishop and C. K. I. Williams, GTM: The generative topographic mapping, Neural Computation, vol. 10, pp. 215–234, 199810.1162/089976698300017953]Search in Google Scholar
[[21] N. Grozavu, Y. Bennani, and M. Lebbah, From variable weighting to cluster characterization in topographic unsupervised learning, in Proc. of IJCNN09, International Joint Conference on Neural Network, 200910.1109/IJCNN.2009.5178666]Search in Google Scholar
[[22] N. Grozavu and Y. Bennani, Topological collaborative clustering, Australian Journal of Intelligent Information Processing Systems, vol. 12, no. 2, 2010]Search in Google Scholar
[[23] J. Sublime, N. Grozavu, G. Cabanes, Y. Bennani, and A. Cornuéjols, From horizontal to vertical collaborative clustering using generative topographic maps, International Journal of Hybrid Intelligent Systems, vol. 12, no. 4, 201610.3233/HIS-160219]Search in Google Scholar
[[24] L. I. Kuncheva and C. J. Whitaker, Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy, Mach. Learn., vol. 51, no. 2, pp. 181–207, May 200310.1023/A:1022859003006]Search in Google Scholar
[[25] F. Gullo, A. Tagarelli, and S. Greco, Diversity-Based Weighting Schemes for Clustering Ensembles, in SDM, 2009, pp. 437–44810.1137/1.9781611972795.38]Search in Google Scholar
[[26] N. Grozavu, M. Ghassany, and Y. Bennani, Learning confidence exchange in collaborative clustering, in Neural Networks (IJCNN), The 2011 International Joint Conference on IEEE, 2011, pp. 872–87910.1109/IJCNN.2011.6033313]Search in Google Scholar
[[27] A. K. Jain and R. C. Dubes, Algorithms for clustering data. Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1988]Search in Google Scholar
[[28] W. M. Rand, Objective criteria for the evaluation of clustering methods, Journal of the American Statistical Association, vol. 66, no. 336, pp. 846–850, Dec. 197110.1080/01621459.1971.10482356]Search in Google Scholar
[[29] L. Hubert and P. Arabie, Comparing Partitions, Journal of the Classification, vol. 2, pp. 193–218, 198510.1007/BF01908075]Search in Google Scholar
[[30] P. Jaccard, The distribution of the flora in the alpine zone, New Phytologist, vol. 11, no. 2, pp. 37–50, 191210.1111/j.1469-8137.1912.tb05611.x]Search in Google Scholar
[[31] D. L. Wallace, A Method for Comparing Two Hierarchical Clusterings: Comment, Journal of the American Statistical Association, vol. 78, no. 383, pp. pp. 569–576, 1983. [Online]. Available: http://www.jstor.org/stable/228811810.2307/2288118]Search in Google Scholar
[[32] F. Pinto, J. Carrico, M. Ramirez, and J. Almeida, Ranked Adjusted Rand: integrating distance and partition information in a measure of clustering agreement, BMC Bioinformatics, vol. 8, no. 1, p. 44, 2007. [Online]. Available: http://www.biomedcentral.com/1471-2105/8/4410.1186/1471-2105-8-44180209317286861]Search in Google Scholar
[[33] I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2005]Search in Google Scholar
[[34] M. Meila, Comparing clusterings - an information based distance, Journal of Multivariate Analysis, vol. 98, pp. 873–895, 200710.1016/j.jmva.2006.11.013]Search in Google Scholar
[[35] A. Frank and A. Asuncion, UCI machine learning repository, 2010. [Online]. Available: http://archive.ics.uci.edu/ml]Search in Google Scholar
[[36] T. Calinski and J. Harabasz, Dendrite method for cluster analysis, Communications in Statistics, vol. 3, no. 1, pp. 1–27, 197410.1080/03610917408548446]Search in Google Scholar
[[37] D. L. Davies and D. W. Bouldin, A cluster separation measure, IEEE Trans. Pattern Anal. Mach. Intell., vol. 1, no. 2, pp. 224–227, Feb. 197910.1109/TPAMI.1979.4766909]Search in Google Scholar
[[38] W. J. Krzanowski and Y. T. Lai, A criterion for determining the number of groups in a data set using sum-of-squares clustering, Biometrics, vol. 44, no. 1, pp. pp. 23–34, 1988. [Online]. Available: http://www.jstor.org/stable/253189310.2307/2531893]Search in Google Scholar
[[39] P. J. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol. 20, no. 0, pp. 53 – 65, 1987. [Online]. Available: http://www.sciencedirect.com/science/article/pii/037704278790125710.1016/0377-0427(87)90125-7]Search in Google Scholar
[[40] K. Kiviluoto, Topology Preservation in Self-Organizing Maps, International Conference on Neural Networks, pp. 294–299, 1996]Search in Google Scholar
[[41] T. Kohonen, Self-Organizing Maps. Berlin: Springer-Verlag, 200110.1007/978-3-642-56927-2]Search in Google Scholar