Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus

Biocybernetics and Biomedical Engineering - Tập 40 - Trang 1-22 - 2020
Namrata Singh1, Pradeep Singh1
1Department of Computer Science and Engineering, National Institute of Technology Raipur, Chhattisgarh, India

Tài liệu tham khảo

Shankaracharya, 2010, Computational intelligence in early diabetes diagnosis: a review, Rev Diabet Stud, 7, 252, 10.1900/RDS.2010.7.252

Erdem, 2005, Ensemble of SVMs for incremental learning, Int Work Mult Classif Syst, 246, 10.1007/11494683_25

Al-Khasawneh, 2015, A method for classification using data mining technique for diabetes: a study of health care information system, Int J Healthc Inf Syst Inform, 10, 1, 10.4018/IJHISI.2015070101

Džeroski, 2004, Is combining classifiers with stacking better than selecting the best one?, Mach Learn, 54, 255, 10.1023/B:MACH.0000015881.36452.6e

Qian, 2015, Pareto ensemble pruning, 2935

Zenobi, 2001, Using diversity in preparing ensembles of classifiers based on different feature subsets to minimize generalization error, Lect Notes Comput Sci, 2167, 576, 10.1007/3-540-44795-4_49

Feller, 1971, 2

Zhang, 2018, Efficient kNN classification with different numbers of nearest neighbors, IEEE Trans Neural Networks Learn Syst, 29, 1774, 10.1109/TNNLS.2017.2673241

Quinlan, 1993

Blake, 1998

Vapnik, 1995

Steinwart, 2006, An explicit description of the reproducing kernel Hilbert spaces of Gaussian RBF kernels, IEEE Trans Inf Theory, 52, 4635, 10.1109/TIT.2006.881713

Rodríguez, 2006, Rotation forest: a New classifier ensemble method, IEEE Trans Pattern Anal Mach Intell, 28, 1619, 10.1109/TPAMI.2006.211

Domeniconi, 2001, Incremental support vector machine construction, 589

Hassab Elgawi, 2007, Online incremental random forests, 102

Guzaitis, 2009, A framework for designing a fuzzy rule-based classifier, 434

Kiziloluk, 2015, Automatic mining of numerical classification rules with parliamentary optimization algorithm, Adv Electr Comput Eng, 15, 17, 10.4316/AECE.2015.04003