Semi-supervised learning for k-dependence Bayesian classifiers
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02531-y.pdf
Reference41 articles.
1. Saadatfar H, Khosravi S, Joloudari J, Mosavi A, Shamshirband S (2020) A new K-Nearest neighbors classifier for big data based on efficient data pruning. Mathematics 8(2):286–302
2. Shao Y, Deng N, Yang Z, Chen W, Wang Z (2012) Probabilistic outputs for twin support vector machines. Knowl Based Syst 33:145–151
3. Tanju O, Kalaylioglu Z (2018) A cluster tree based model selection approach for logistic regression classifier. J Stat Comput Simul 88:1394–1414
4. Zhang Y, Lu S, Zhou X, Yang M, Wu L, Liu B, Phillips P, Wang S (2016) Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: decision tree, k-nearest neighbors, and support vector machine. Simulation 92:861–871
5. Liu Y, Wang L, Mammadov M (2020) Learning semi-lazy Bayesian network classifier under the c.i.i.d assumption. Knowledge-Based Systems. https://doi.org/10.1016/j.knosys.2020.106422
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