@inproceedings{397872c4dc2a496492eeb55805859779,
title = "A self-adaptive Bayesian network classifier by means of genetic optimization",
abstract = "In the design of conventional Bayes network classifiers (e.g. Naive Bayes Classifier, Tree Augment Naive Bayes classifier), the network classifier structures are always fixed. Such network structures are very difficult to reflect the relationships among nodes (attributes). In this paper, we propose a self-adaptive Bayesian Network classifier based on genetic optimization. Genetic optimization is exploited here to realize the Self-adaptiveness, which means the network structure can be gradually optimized when constructing Bayesian network classifier. Experimental results show that the proposed method leads to a high classification accuracy than Naive Bayes classifier, Tree Augment Naive Bayes classifier, and KNN classifier on some benchmarks.",
keywords = "Bayesian Network, Genetic optimization, network structrue, self-adaptive",
author = "Hongshui Xu and Wei Huang and Jinsong Wang and Dan Wang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 8th IEEE International Conference on Software Engineering and Service Science, ICSESS 2017 ; Conference date: 24-11-2017 Through 26-11-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICSESS.2017.8343007",
language = "English",
series = "Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS",
publisher = "IEEE Computer Society",
pages = "688--691",
editor = "Li Wenzheng and Babu, {M. Surendra Prasad} and Lei Xiaohui",
booktitle = "ICSESS 2017 - Proceedings of 2017 IEEE 8th International Conference on Software Engineering and Service Science",
address = "United States",
}