Least squares approach to K-SVCR multi-class classification with its applications
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10472-021-09747-1.pdf
Reference38 articles.
1. Boser, B.E., Guyon, I.M., Vapnik, V.: A training algorithm for optimal margin classifiers. In: Proceedings of the fifth annual workshop on Computational learning theory, COLT ’92, pp 144–152. Association for Computing Machinery, New York (1992)
2. Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20 (3), 273–297 (1995). https://doi.org/10.1007/BF00994018
3. Déniz, O., Castrillon, M., Hernández, M.: Face recognition using independent component analysis and support vector machines. Pattern Recogn. Lett. 24(13), 2153–2157 (2003)
4. Arabasadi, Z., Alizadehsani, R., Roshanzamir, M., Moosaei, H., Yarifard, A.A.: Computer aided decision making for heart disease detection using hybrid neural network-genetic algorithm. Comput. Methods Programs Biomed. 141, 19–26 (2017)
5. Ahmad, A.S., Hassan, M.Y., Abdullah, M.P., Rahman, H.A., Hussin, F., Abdullah, H., Saidur, R.: A review on applications of ANN and SVM for building electrical energy consumption forecasting. Renew. Sustain. Energy Rev. 33, 102–109 (2014)
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