A genetic algorithm-based feature selection. International Journal of Electronics Communication and Computer Engineering 2014; 5(4):889-905.B. Oluleye, L. Armstrong, J. Leng, D. Diepeveen, A genetic algorithm-based fea- ture selection, Int. J. Electr. Commun. Comput. Eng. 5 (4) (2014)...
Wrapper framework for feature selection We consider designing a hybrid genetic algorithm within the wrapper framework in order to solve the feature selection problem in the context of pattern classification based on mutual information. In general, a pattern classification problem can be described as foll...
Cite this chapter Huang, J., Rong, P. (2009). A Hybrid Genetic Algorithm for Feature Selection Based on Mutual Information. In: Emmert-Streib, F., Dehmer, M. (eds) Information Theory and Statistical Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-84816-7_6 Download...
Multi-objective genetic algorithmWith the expansion of data size and data dimension, feature selection attracts more and more attention. In this paper, we propose a novel feature selection algorithm, namely, Hybrid filter and Symmetrical Complementary Coefficient based Multi-Objective Genetic Algorithm ...
This paper proposes a method of genetic algorithm (GA) based neural network for feature selection that retains sufficient information for classification purposes. This method combines a genetic algorithm with an artificial neural network classifier, such as back-propagation (BP) neural classifier, radial...
Khammassi and Krichen propose a GA-LR wrapper approach for feature selection in network intrusion detection [16]. They used a genetic algorithm-based packing method as a search strategy and logistic regression as a learning algorithm to select the best subset of features. Moreover, the method ef...
A Classification Error Impurity (CEI) algorithm is proposed as a frequency-based filter ranker. • An Adaptive Genetic Algorithm with an External Repository (AGAwER) is proposed as a wrapper method to augment the exploration of GA. • It is explored that the ensemble of the top features ob...
遗传算法(Genetic Algorithm, GA)是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型,是一种通过模拟自然进化过程搜索最优解的方法。 其主要特点是直接对结构对象进行操作,不存在求导和函数连续性的限定;具有内在的隐并行性和更好的全局寻优能力;采用概率化的寻优方法,不需要确定的规则就能自动获取...
遗传算法(Genetic Algorithm, GA)是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型,是一种通过模拟自然进化过程搜索最优解的方法。 其主要特点是直接对结构对象进行操作,不存在求导和函数连续性的限定;具有内在的隐并行性和更好的全局寻优能力;采用概率化的寻优方法,不需要确定的规则就能自动获取...
Nguyen MH, Le Nguyen P, Nguyen K, Le VA, Nguyen T-H, Ji Y (2021) PM2.5 prediction using genetic algorithm-based feature selection and encoder-decoder model. IEEE Access 9:57338–57350. https://doi.org/10.1109/ACCESS.2021.3072280 Article Google Scholar Ni S, Jia P, Xu Y, Zeng L,...