Abstract
Data mining has been gaining widespread significance in recent times with the ever-increasing volume of data to be handled and processed in real time scenarios. This research paper investigates a hybrid scheme of data mining implemented for a classification problem on a repository consisting of large volumes of data. A hidden Markov model (HMM) has been utilized for modeling the high dimensional data pool and classification achieved using a naive bayesian classifier. A data repository with four different subjects and 50,000 instances has been mined using the proposed hybrid algorithm and compared against recent mining techniques like radial neural network and bayesian models and superior performance in terms of classification accuracy, computation time has been observed and reported.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Setiono, R., Baesens, B., Mues, C.: A note on knowledge discovery using neural networks and its application to credit screening. Eur. J. Oper. Res. 192, 326–332 (2009)
Kiani, R., Mahdavi, S., Keshavarzi, A.: Analysis and prediction of crimes by clustering and classification. Int. J. Adv. Res. Artif. Intell. 4(8), 11–17 (2015)
Thomassey, S., Fiordaliso, A.: A hybrid sales forecasting system based on clustering and decision trees. Decis. Support Syst. 42, 408–421 (2006)
Kagdi, H., Collard, M.L., Maletic, J.I.: A survey and taxonomy of approaches for mining software repositories in the context of software evolution. J. Softw. Maint. Evol.: Res. Pract. 19, 77–131 (2007)
Das, P., Das, A.K.: Behavioural analysis of crime against women using a graph based clustering approach. In: International Conference on Computer Communication and Informatics, pp. 1–6 (2017)
Kamruzzaman, S.M., Jehad Sarkar, A.M.: A new data mining scheme using artificial neural networks. Sens. J. 11(5), 4622–4647 (2011)
Patel, S., Patel, H.: Survey on data mining techniques used in healthcare domain. Int. J. Inf. Sci. Tech. 6(1), 53–60 (2016)
Cole, S., Tidke, B.: A survey of big data in social media using data mining techniques. In: Proceedings of International Conference on Advanced Computing and Communication Systems (2015)
Phyu, T.N.: Survey of classification techniques in data mining. In: Proceedings of the International Multi-Conference of Engineers and Computer Scientists, vol. 1, pp. 1–5 (2009)
Law, H.C.M., Figueiredo, A.T.M., Jain Anil, K.: Simultaneous feature selection and clustering using mixture models. IEEE Trans. Pattern Anal. Mach. Intell. 26(9), 1154–1166 (2004)
Mucherino, A., Papajorgji, P., Pardalos, P.M.: A survey of data mining techniques applied to agriculture. Oper. Res. Int. J. 9(2), 121–140 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Krubakaran, C., Venkatachalapathy, K. (2019). Research on a Novel B-HMM Model for Data Mining in Classification of Large Dimensional Data. In: Smys, S., Bestak, R., Chen, JZ., Kotuliak, I. (eds) International Conference on Computer Networks and Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 15. Springer, Singapore. https://doi.org/10.1007/978-981-10-8681-6_88
Download citation
DOI: https://doi.org/10.1007/978-981-10-8681-6_88
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8680-9
Online ISBN: 978-981-10-8681-6
eBook Packages: EngineeringEngineering (R0)