Abstract
The paper proposes tools for data dimensionality reduction containing sample selection method and instance informativity indicators based on the evolutionary search, which is modified to speed up the search through the creation of special operators, taking into account a priori information about the data sample and concentrating search on the most perspective solution areas. This allows preserving the stochastic nature of the search to accelerate the obtainment of acceptable solutions through the introduction of deterministic component in the search strategy. The proposed methods are experimentally studied. On the results of experiments the comparative characteristics and recommendations for the use of the proposed methods are given.
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
References
Lavrakas, P.J.: Encyclopedia of Survey Research Methods. Sage Publications, Thousand Oaks (2008)
Korobiichuk, I., Podchashinskiy, Y., Shapovalova, O., Shadura, V., Nowicki, M., Szewczyk, R.: Precision increase in automated digital image measurement systems of geometric values. In: Jabłoński, R., Brezina, T. (eds.) Advanced Mechatronics Solutions. AISC, vol. 393, pp. 335–340. Springer, Heidelberg (2016). doi:10.1007/978-3-319-23923-1_51
Hansen, M.H., Hurtz, W.N., Madow, W.G.: Sample Survey Methods and Theory. Wiley, New York (1953)
Bernard, H.R.: Social Research Methods: Qualitative and Quantitative Approaches. Sage Publications, Thousand Oaks (2006)
Korobiichuk, I., Bezvesilna, O., Ilchenko, A., Shadura, V., Nowicki, M., Szewczyk, R.: A mathematical model of the thermo-anemometric flowmeter. Sensors 15, 22899–22913 (2015). doi:10.3390/s150922899
Subbotin, S.: The instance and feature selection for neural network based diagnosis of chronic obstructive bronchitis. In: Bris, R., Majernik, J., Pancerz, K., Zaitseva, E. (eds.) Applications of Computational Intelligence in Biomedical Technology. SCI, vol. 606, pp. 215–228. Springer, Heidelberg (2016). doi:10.1007/978-3-319-19147-8_13
Ghosh, S.: Multivariate Analysis, Design of Experiments, and Survey Sampling. Marcel Dekker Inc., New York (1999)
Subbotin, S.A.: The training set quality measures for neural network learning. Opt. Memory Neural Netw. (Inf. Opt.) 2(19), 126–139 (2010)
Smith, G.: A deterministic approach to partitioning neural network training data for the classification problem: dissertation. Virginia Polytechnic Institute & State University, Blacksburg (2006)
Subbotin, S.A.: The sample properties evaluation for pattern recognition and intelligent diagnosis. In: 10th International Conference on Digital Technologies, pp. 321–332. IEEE, Zilina (2014)
Plutowski, M.: Selecting training exemplars for neural network learning: dissertation. University of California, San Diego (1994)
Oliinyk, A., Zaiko, T., Subbotin, S.: Training sample reduction based on association rules for neuro-fuzzy networks synthesis. Opt. Memory Neural Netw. (Inf. Opt.) 2(23), 89–95 (2014)
Chaudhuri, A., Stenger, H.: Survey Sampling Theory and Methods. Chapman & Hall, New York (2005)
Subbotin, S.A.: Methods of sampling based on exhaustive and evolutionary search. Autom. Control Comput. Sci. 3(47), 113–121 (2013)
Tenne, Y., Goh, C.-K.: Computational Intelligence in Expensive Optimization Problems. Springer, Berlin (2010)
Talbi, E.: Metaheuristics: from Design to Implementation. Wiley, Hoboken (2009)
Iris Data Set. https://archive.ics.uci.edu/ml/datasets/Iris
Acknowledgements
This paper is prepared with partial support of “Centers of Excellence for young RESearchers” (CERES) project (Reference Number 544137-TEMPUS-1-2013-1-SK-TEMPUS-JPHES) of Tempus Programme of the European Union.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Subbotin, S., Oliinyk, A. (2017). The Sample and Instance Selection for Data Dimensionality Reduction. In: Szewczyk, R., Kaliczyńska, M. (eds) Recent Advances in Systems, Control and Information Technology. SCIT 2016. Advances in Intelligent Systems and Computing, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-319-48923-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-48923-0_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48922-3
Online ISBN: 978-3-319-48923-0
eBook Packages: EngineeringEngineering (R0)