In this paper, we design a genetic algorithm-based feature selection method for ICS characteristics. The proposed method incorporates a feature ranking fusion mechanism in the genetic algorithm for eliminating
Feature selection aims to reduce the dimensionality of patterns for clas-sificatory analysis by selecting the most informative rather than irrelevant and/or redundant features. In this study, a hybrid genetic algorithm for feature selection is presented
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...
Then, the improved neighborhood rough set with sample granulation (INRSG) is proposed under different granular radius, which further improves the quality of the feature subset. Finally, in order to find out the optimal granular radius, granularity 位 optimization based on genetic algorithm (ROGA) ...
(ii) wrapper-based These methods evaluate usefulness of selected features using learner's performance [9]. In a separate study, a feature selection method was proposed in which both unbalanced and balanced data can be classified, based on a genetic algorithm. However, it has been proved that ...
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...
Recursive 385 Feature Elimination; rfGA: 'Random Forest'-based Genetic Algorithm; RNA-Seq: RNA Sequencing; ROC: Receiver Operating Characteristic; SBF: Selection By Filtering; SEN: Sensitivity; SPE: Specificity; svmGA: 'Support Vector Machine'- based Genetic Algorithm; T: tumors Acknowledgements Not...
Khan, M. A.An optimized method for segmentation and classification of apple diseases based on strong correlation and genetic algorithm based feature selection.IEEE Access7, 46261–46277 (2019). ArticleGoogle Scholar Xue, X., Li, C., Cao, S., Sun, J. & Liu, L. Fault diagnosis of rolling...
Distance-based Mutual Congestion Genetic Algorithm with Adaptive Rates (DMC-GAwAR) [17] merged the filter frequency-based DMC with the wrapper GAwAR and was designed for binary datasets. Given DMC’s consideration of feature values alongside feature frequency, it outperformed other frequency-based rank...