https://oldena.lpnu.ua/handle/ntb/52497| Title: | Piecewise-Linear Approach to Classification Based on Geometrical Transformation Model for Imbalanced Dataset |
| Authors: | Doroshenko, Anastasiya |
| Affiliation: | Lviv Polytechnic National University |
| Bibliographic description (Ukraine): | 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). |
| Bibliographic description (International): | 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). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | data mining classification imbalanced data neural-like structure of successive geometric transformations model NLS SGTM cost sensitive classification |
| Number of pages: | 5 |
| Page range: | 231-235 |
| Start page: | 231 |
| End page: | 235 |
| 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. |
| URI: | https://ena.lpnu.ua/handle/ntb/52497 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://doi.org/10.1007/978-3-319-91008-6_12 |
| References (Ukraine): | [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. [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 [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 [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. [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. [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 [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 [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. [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). [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. [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 [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 [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. [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. |
| References (International): | [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. [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 [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 [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. [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. [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 [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 [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. [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). [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. [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 [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 [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. [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. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Doroshenko_A-Piecewise_Linear_Approach_231-235.pdf | 305.6 kB | Adobe PDF | View/Open | |
| 2018_Doroshenko_A-Piecewise_Linear_Approach_231-235__COVER.png | 1.44 MB | image/png | View/Open |
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