| DC Field | Value | Language |
|---|
| dc.contributor.author | Doroshenko, Anastasiya | |
| dc.coverage.temporal | 21-25 August 2018, Lviv | |
| dc.date.accessioned | 2020-06-19T12:05:17Z | - |
| dc.date.available | 2020-06-19T12:05:17Z | - |
| dc.date.created | 2018-02-28 | |
| dc.date.issued | 2018-02-28 | |
| dc.identifier.citation | Doroshenko A. Piecewise-Linear Approach to Classification Based on Geometrical Transformation Model for Imbalanced Dataset / Anastasiya Doroshenko // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 231–235. — (Dynamic Data Mining & Data Stream Mining). | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52497 | - |
| dc.description.abstract | The article describes the method of cost-sensitive
classification for imbalanced dataset based on neural-like
structure of successive geometric transformations model using
piecewise-linear approach to classification. The proposed
method characterized by high learning speed and accuracy of
classification. | |
| dc.format.extent | 231-235 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 | |
| dc.relation.uri | https://doi.org/10.1007/978-3-319-91008-6_12 | |
| dc.subject | data mining | |
| dc.subject | classification | |
| dc.subject | imbalanced data | |
| dc.subject | neural-like structure of successive geometric transformations model | |
| dc.subject | NLS SGTM | |
| dc.subject | cost sensitive classification | |
| dc.title | Piecewise-Linear Approach to Classification Based on Geometrical Transformation Model for Imbalanced Dataset | |
| dc.type | Conference Abstract | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2018 | |
| dc.contributor.affiliation | Lviv Polytechnic National University | |
| dc.format.pages | 5 | |
| dc.identifier.citationen | Doroshenko A. Piecewise-Linear Approach to Classification Based on Geometrical Transformation Model for Imbalanced Dataset / Anastasiya Doroshenko // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 231–235. — (Dynamic Data Mining & Data Stream Mining). | |
| dc.relation.references | [1] C. C. Aggarwal and P. S. Yu, "A Survey of Uncertain Data Algorithms and Applications," IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 5, pp. 609-623, May 2009. | |
| dc.relation.references | [2] A. J. Chamatkar and P. K. Butey, "Implementation of Different Data Mining Algorithms with Neural Network," 2015 International Conference on Computing Communication Control and Automation, Pune, pp. 374-378, 2015. doi: 10.1109/ICCUBEA.2015.78 | |
| dc.relation.references | [3] D. Zhu, H. Jin, Y. Yang, D. Wu and W. Chen, "DeepFlow: Deep learning-based malware detection by mining Android application for abnormal usage of sensitive data," 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, pp. 438-443, 2017. doi: 10.1109/ISCC.2017.8024568 | |
| dc.relation.references | [4] Ye. Bodyanskiy, I. Perova, O. Vynokurova, and I. Izonin “Adaptive Wavelet Diagnostic Neuro-Fuzzy System for Biomedical Tasks,” 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, 299-303, February 20 – 24, 2018. | |
| dc.relation.references | [5] O. Riznik, I. Yurchak, E. Vdovenko and A. Korchagina, "Model of stegosystem images on the basis of pseudonoise codes," VIth International Conference on Perspective Technologies and Methods in MEMS Design, Lviv, pp. 51-52, 2010. | |
| dc.relation.references | [6] R. Tkachenko, . Doroshenko, I. Izonin, Y. Tsymbal, and B. Havrysh, “Imbalance Data Classification via Neural-like Structures of Geometric Transformations Model: Local and Global Approaches,” In: Hu, Z. B., Petoukhov, S., (eds) Advances in Computer Science for Engineering and Education. ICCSEEA2018. Advances in Intelligent Systems and Computing. Springer, Cham, vol.754, pp.112-122, 2018. https://doi.org/10.1007/978-3-319-91008-6_12 | |
| dc.relation.references | [7] A. D. Pozzolo, O. Caelen, R. A. Johnson and G. Bontempi, "Calibrating Probability with Undersampling for Unbalanced Classification," IEEE Symposium Series on Computational Intelligence, Cape Town, pp. 159-166, 2015. doi: 10.1109/SSCI.2015.33 | |
| dc.relation.references | [8] J. Wang, P. Zhao and S. C. H. Hoi, "Cost-Sensitive Online Classification," IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 10, pp. 2425-2438, Oct. 2014. | |
| dc.relation.references | [9] R. Tkachenko and I. Izonin “Model and Principles for the Implementation of Neural-Like Structures based on Geometric Data Transformations”, In: Hu, Z.B., Petoukhov, S., Advances in Computer Science for Engineering and Education. ICCSEEA2018. Advances in Intelligent Systems and Computing. Springer, Cham (2018). | |
| dc.relation.references | [10] S. Ghosh, A. Ray, D. Yadav and B. M. Karan, "A Genetic Algorithm Based Clustering Approach for Piecewise Linearization of Nonlinear Functions," 2011 International Conference on Devices and Communications, Mesra, pp. 1-4, 2011. | |
| dc.relation.references | [11] H. He and E. A. Garcia, "Learning from Imbalanced Data," in IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 9, pp. 1263-1284, Sept. 2009. doi: 10.1109/TKDE.2008.239 | |
| dc.relation.references | [12] R. Tkachenko, H. Cutucu, I. Izonin, A. Doroshenko, and Yu. Tsymbal ‘Non-iterative Neural-like Predictor for Solar Energy in Libya,” In: Ermolayev, V., Suárez-Figueroa, M. C., Ławrynowicz, A., Palma, R., Yakovyna, V., Mayr, H. C., Nikitchenko, M., and Spivakovsky, A. (Eds.): ICT in Education, Research and Industrial Applications. Proc. 14-th Int. Conf. ICTERI 2018. Volume I: Main Conference. Kyiv, Ukraine, May 14-17, pp.35-45, 2018, CEUR-WS.org | |
| dc.relation.references | [13] U. Polishchuk, P. Tkachenko, R. Tkachenko and I. Yurchak, "Features of the auto-associative neurolike structures of the geometrical transformation machine (GTM)," 2009 5th International Conference on Perspective Technologies and Methods in MEMS Design, Zakarpattya, Ukrane, pp. 66-67, 2009. | |
| dc.relation.references | [14] R. Tkachenko, I. Yurchak and U. Polishchuk, "Neurolike networks on the basis of Geometrical Transformation Machine," 2008 International Conference on Perspective Technologies and Methods in MEMS Design, Polyana, Ukrane, pp. 77-80, 2008. doi: 10.1109/MEMSTECH.2008.4558743. | |
| dc.relation.referencesen | [1] C. C. Aggarwal and P. S. Yu, "A Survey of Uncertain Data Algorithms and Applications," IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 5, pp. 609-623, May 2009. | |
| dc.relation.referencesen | [2] A. J. Chamatkar and P. K. Butey, "Implementation of Different Data Mining Algorithms with Neural Network," 2015 International Conference on Computing Communication Control and Automation, Pune, pp. 374-378, 2015. doi: 10.1109/ICCUBEA.2015.78 | |
| dc.relation.referencesen | [3] D. Zhu, H. Jin, Y. Yang, D. Wu and W. Chen, "DeepFlow: Deep learning-based malware detection by mining Android application for abnormal usage of sensitive data," 2017 IEEE Symposium on Computers and Communications (ISCC), Heraklion, pp. 438-443, 2017. doi: 10.1109/ISCC.2017.8024568 | |
| dc.relation.referencesen | [4] Ye. Bodyanskiy, I. Perova, O. Vynokurova, and I. Izonin "Adaptive Wavelet Diagnostic Neuro-Fuzzy System for Biomedical Tasks," 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, 299-303, February 20 – 24, 2018. | |
| dc.relation.referencesen | [5] O. Riznik, I. Yurchak, E. Vdovenko and A. Korchagina, "Model of stegosystem images on the basis of pseudonoise codes," VIth International Conference on Perspective Technologies and Methods in MEMS Design, Lviv, pp. 51-52, 2010. | |
| dc.relation.referencesen | [6] R. Tkachenko, . Doroshenko, I. Izonin, Y. Tsymbal, and B. Havrysh, "Imbalance Data Classification via Neural-like Structures of Geometric Transformations Model: Local and Global Approaches," In: Hu, Z. B., Petoukhov, S., (eds) Advances in Computer Science for Engineering and Education. ICCSEEA2018. Advances in Intelligent Systems and Computing. Springer, Cham, vol.754, pp.112-122, 2018. https://doi.org/10.1007/978-3-319-91008-6_12 | |
| dc.relation.referencesen | [7] A. D. Pozzolo, O. Caelen, R. A. Johnson and G. Bontempi, "Calibrating Probability with Undersampling for Unbalanced Classification," IEEE Symposium Series on Computational Intelligence, Cape Town, pp. 159-166, 2015. doi: 10.1109/SSCI.2015.33 | |
| dc.relation.referencesen | [8] J. Wang, P. Zhao and S. C. H. Hoi, "Cost-Sensitive Online Classification," IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 10, pp. 2425-2438, Oct. 2014. | |
| dc.relation.referencesen | [9] R. Tkachenko and I. Izonin "Model and Principles for the Implementation of Neural-Like Structures based on Geometric Data Transformations", In: Hu, Z.B., Petoukhov, S., Advances in Computer Science for Engineering and Education. ICCSEEA2018. Advances in Intelligent Systems and Computing. Springer, Cham (2018). | |
| dc.relation.referencesen | [10] S. Ghosh, A. Ray, D. Yadav and B. M. Karan, "A Genetic Algorithm Based Clustering Approach for Piecewise Linearization of Nonlinear Functions," 2011 International Conference on Devices and Communications, Mesra, pp. 1-4, 2011. | |
| dc.relation.referencesen | [11] H. He and E. A. Garcia, "Learning from Imbalanced Data," in IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 9, pp. 1263-1284, Sept. 2009. doi: 10.1109/TKDE.2008.239 | |
| dc.relation.referencesen | [12] R. Tkachenko, H. Cutucu, I. Izonin, A. Doroshenko, and Yu. Tsymbal ‘Non-iterative Neural-like Predictor for Solar Energy in Libya," In: Ermolayev, V., Suárez-Figueroa, M. C., Ławrynowicz, A., Palma, R., Yakovyna, V., Mayr, H. C., Nikitchenko, M., and Spivakovsky, A. (Eds.): ICT in Education, Research and Industrial Applications. Proc. 14-th Int. Conf. ICTERI 2018. Volume I: Main Conference. Kyiv, Ukraine, May 14-17, pp.35-45, 2018, CEUR-WS.org | |
| dc.relation.referencesen | [13] U. Polishchuk, P. Tkachenko, R. Tkachenko and I. Yurchak, "Features of the auto-associative neurolike structures of the geometrical transformation machine (GTM)," 2009 5th International Conference on Perspective Technologies and Methods in MEMS Design, Zakarpattya, Ukrane, pp. 66-67, 2009. | |
| dc.relation.referencesen | [14] R. Tkachenko, I. Yurchak and U. Polishchuk, "Neurolike networks on the basis of Geometrical Transformation Machine," 2008 International Conference on Perspective Technologies and Methods in MEMS Design, Polyana, Ukrane, pp. 77-80, 2008. doi: 10.1109/MEMSTECH.2008.4558743. | |
| dc.citation.conference | IEEE second international conference "Data stream mining and processing" | |
| dc.citation.spage | 231 | |
| dc.citation.epage | 235 | |
| dc.coverage.placename | Львів | |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference
|
