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In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine., , , and . Neural Processing Letters, 36 (3): 275-283 (2012)Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities., , , and . IJCNN, page 3916-3921. IEEE, (2014)Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory., , , , and . IJCNN, page 1-8. IEEE, (2010)PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis., , and . Pattern Recognit. Lett., (2016)A Machine Learning Analysis of Health Records of Patients With Chronic Kidney Disease at Risk of Cardiovascular Disease., , and . IEEE Access, (2021)Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma., and . Health Informatics J., 27 (1): 146045822098420 (2021)Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic., , , , and . J. Univers. Comput. Sci., 19 (9): 1295-1314 (2013)An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data., and . IEEE ACM Trans. Comput. Biol. Bioinform., 18 (6): 2759-2765 (2021)Nested Sequential Minimal Optimization for Support Vector Machines., , , , and . ICANN (2), volume 7553 of Lecture Notes in Computer Science, page 156-163. Springer, (2012)Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids., , , , and . IEEE Syst. J., 12 (3): 2842-2853 (2018)