Abstract
The paper combines distance-based weak classifiers constructed using kernel fuzzy clustering technique with the naive Bayes algorithm. Resulting hybrid online ensemble is validated through computational experiment involving a number of datasets often used for testing data streams mining algorithms.
Keywords
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References
Asuncion, A., Newman, D.J.: UCI Machine Learning Repository. University of California, School of Information and Computer Science (2007). http://www.ics.uci.edu/ mlearn/MLRepository.html
Bertini, J.R., Zhao, L., Lopes, A.: An Incremental Learning Algorithm Based on the K-associated Graph for Non-stationary Data Classification. Information Sciences 246, 52–68 (2013)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Kluwer Academic Publishers (1981)
Chiang, J.H., Hao, P.Y.: A new kernel-based fuzzy clustering approach: support vector clustering with cell growing. IEEE T. Fuzzy Systems 11(4), 518–527 (2003)
Gaber, M.M., Zaslavsky, A., Krishnaswamy, S.: Data stream mining. In: Maimon, O., Rokach, L. (eds.) Data Mining and Knowledge Discovery Handbook, Part 6, pp. 759–787 (2010)
Graves, D., Pedrycz, W.: Kernel-based Fuzzy Clustering and Fuzzy clustering: A Comparative Experimental Study. Fuzzy Sets and Systems 161(4), 522–543 (2010)
Jędrzejowicz, J., Jędrzejowicz, P.: Online classifiers based on fuzzy C-means clustering. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds.) ICCCI 2013. LNCS, vol. 8083, pp. 427–436. Springer, Heidelberg (2013)
Jędrzejowicz, J., Jędrzejowicz, P.: A family of the online distance-based classifiers. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds.) ACIIDS 2014, Part II. LNCS, vol. 8398, pp. 177–186. Springer, Heidelberg (2014)
Li, Z., Tang, S., Xue, J., Jiang, J.: Modified FCM Clustering Based on Kernel Mapping. Proc. SPIE 4554, 241–245 (2001)
Lopes, N., Ribeiro, B.: Machine Learning for Adaptive Many-core Machines: A Practical Approach, Studies in Big Data 7. Springer International Publishing (2015)
Machine Learning Data Set Repository (2013). http://mldata.org/repository/tags/data/IDA_Benchmark_Repository/
Mena-Torres, D., Aguilar-Ruiz, J.S.: A Similarity-based Approach for Data Stream Classification. Expert Systems with Applications 41, 4224–4234 (2014)
Moreno-Torres, J.G., Sáez, J.A., Herrera, F.: Study on the Impact of Partition-Induced Dataset Shift on k-Fold Cross-Validation. IEEE Trans. Neural Netw. Learning Syst. 23(8), 1304–1312 (2012)
Pramod, S., Vyas, O.P.: Data Stream Mining: A Review on Windowing Approach. Global Journal of Computer Science and Technology Software & Data Engineering 12(11), 26–30 (2012)
Turkov, P., Krasotkina, O., Mottl, V.: Dynamic programming for bayesian logistic regression learning under concept drift. In: Maji, P., Ghosh, A., Murty, M.N., Ghosh, K., Pal, S.K. (eds.) PReMI 2013. LNCS, vol. 8251, pp. 190–195. Springer, Heidelberg (2013)
Waikato (2013). http://moa.cms.waikato.ac.nz/datasets/
Wang, L., Ji, H.-B., Jin, Y.: Fuzzy Passive-Aggressive Classification: A Robust and Efficient Algorithm for Online Classification Problems. Information Sciences 220, 46–63 (2013)
Wisaeng, K.: A Comparison of Different Classification Techniques for Bank Direct Marketing. International Journal of Soft Computing and Engineering 3(4), 116–119 (2013)
Wilson, D.R., Martinez, T.R.: Improved Heterogeneous Distance Functions. Journal of Artificial Intell. Research 6, 1–34 (1997)
Zhang, D., Chen, S.: Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm. Neural Processing Letters 18(3), 155–162 (2003)
Zhang, D., Chen, S.: Fuzzy clustering using kernel method. In: Proc. International Conference on Control and Automation ICCA, Xiamen, China, pp. 162–163 (2002)
Žliobaite, I.: Combining Similarity in Time and Space for Training Set Formation under Concept Drift. Intelligent Data Analysis 15(4), 589–611 (2011)
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Jȩdrzejowicz, J., Jȩdrzejowicz, P. (2015). A Hybrid Distance-Based and Naive Bayes Online Classifier. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9330. Springer, Cham. https://doi.org/10.1007/978-3-319-24306-1_21
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DOI: https://doi.org/10.1007/978-3-319-24306-1_21
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