Scalable Learning of k-dependence Bayesian Classifiers under MapReduce

Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015

Volumn 2, Issue , 2015, Pages 25-32

  Arias, Jacinto ^a   Gamez, Jose A ^a   Puerta, Jose M ^a  

^a UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COMPLEX NETWORKS; DATA MINING; DIGITAL STORAGE; PARALLEL ARCHITECTURES;

BAYESIAN CLASSIFIER; BIG DATA APPLICATIONS; COMPUTATIONAL PARADIGM; EMERGENT TECHNOLOGIES; EXPERIMENTAL EVALUATION; HIGH-DIMENSIONAL PROBLEMS; MAPREDUCE FRAMEWORKS; SUPERVISED CLASSIFICATION;

BIG DATA;

EID: 84969135956     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/Trustcom.2015.558     Document Type: Conference Paper

References (24)

1. T. White, Hadoop: the definitive guide: the definitive guide. " O'Reilly Media, Inc.", 2009.
2. J. Dean and S. Ghemawat, "MapReduce: simplified data processing on large clusters," Communications of the ACM, pp. 1-13, 2008.
3. M. Zaharia, M. Chowdhury, M. J. Franklin, S. Shenker, I. Stoica, "Spark: cluster computing with working sets," in Proceedings of the 2nd USENIX conference on Hot topics in cloud computing, 2010, pp. 10-10.
4. N. Friedman, D. Geiger, M. Goldszmidt, "Bayesian network classifiers," Machine learning, vol. 163, pp. 131-163, 1997.
5. F. V. Jensen and T. D. Nielsen, Bayesian Networks and Decision Graphs, 2nd ed. Springer Publishing Company, Incorporated, 2007.
6. M. Sahami, "Learning Limited Dependence Bayesian Classifiers," KDD, no. Cix, pp. 335-338, 1996.
7. M. J. Flores, J. A. Gamez, A. M. Martnez, J. M. Puerta, "Handling numeric attributes when comparing bayesian network classifiers: does the discretization method matter" Appl. Intell., vol. 34, no. 3, pp. 372-385, 2011.
8. A. L. Madsen, F. Jensen, A. Salmeron, M. Karlsen, H. Langseth, T. D. Nielsen, "A new method for vertical parallelisation of TAN learning based on balanced incomplete block designs," in Probabilistic Graphical Models-7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings, 2014, pp. 302-317.
9. A. X. Tan, V. L. Liu, M. Kantarcioglu, B. Thuraisingham, "A comparison of approaches for large-scale data mining," Technical Report UTDCS-24-10, Tech. Rep., 2010.
10. B. Liu, E. Blasch, Y. Chen, D. Shen, G. Chen, "Scalable sentiment classification for big data analysis using naive bayes classifier," in Big Data, 2013 IEEE International Conference on. IEEE, 2013, pp. 99-104.
11. A. Basak, I. Brinster, X. Ma, O. J. Mengshoel, "Accelerating bayesian network parameter learning using hadoop and mapreduce," in Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications. ACM, 2012, pp. 101-108.
12. J. Pearl, Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, 2014.
13. R. R. E. Neapolitan, Learning bayesian networks. Prentice-Hall, Inc., Apr. 2003.
14. J. Arias, J. A. Gamez, J. M. Puerta, "Structural learning of bayesian networks via constrained hill climbing algorithms: Adjusting trade-off between efficiency and accuracy," International Journal of Intelligent Systems, vol. 30, no. 3, pp. 292-325, 2015.
15. C. Bielza and P. Larranaga, "Discrete bayesian network classifiers: a survey," ACM Computing Surveys (CSUR), vol. 47, no. 1, p. 5, 2014.
16. R. C. Taylor, "An overview of the hadoop/mapreduce/hbase framework and its current applications in bioinformatics," BMC bioinformatics, vol. 11, no. Suppl 12, p. S1, 2010.
17. D. P. Wall, P. Kudtarkar, V. A. Fusaro, R. Pivovarov, P. Patil, P. J. Tonellato, "Cloud computing for comparative genomics," BMC bioinformatics, vol. 11, no. 1, p. 259, 2010.
18. X. Qiu, J. Ekanayake, S. Beason, T. Gunarathne, G. Fox, R. Barga, D. Gannon, "Cloud technologies for bioinformatics applications," in Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers. ACM, 2009, p. 6.
19. A. Goyal, F. Bonchi, L. V. Lakshmanan, "Learning influence probabilities in social networks," in Proceedings of the third ACM international conference on Web search and data mining. ACM, 2010, pp. 241-250.
20. M. Shmueli-Scheuer, H. Roitman, D. Carmel, Y. Mass, D. Konopnicki, "Extracting user profiles from large scale data," in Proceedings of the 2010 Workshop on Massive Data Analytics on the Cloud. ACM, 2010, p. 4.
21. V. Bolon-Canedo, N. Sanchez-Maroño, A. Alonso-Betanzos, J. Bentez, F. Herrera, "A review of microarray datasets and applied feature selection methods," Information Sciences, vol. 282, pp. 111-135, 2014.
22. S. Sonnenburg and V. Franc, "Coffin: A computational framework for linear svms," 2010.
23. J. Bacardit, P. Widera, A. Marquez-Chamorro, F. Divina, J. S. Aguilar-Ruiz, N. Krasnogor, "Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features," Bioinformatics, vol. 28, no. 19, pp. 2441-2448, 2012.
24. G.-X. Yuan, C.-H. Ho, C.-J. Lin, "An improved glmnet for l1-regularized logistic regression," The Journal of Machine Learning Research, vol. 13, no. 1, pp. 1999-2030, 2012.