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What is An Evolutionary Correlation-Aware Feature Selection Method For Classification Problems about?

This paper presents an estimation of distribution algorithm (EDA)-based feature selection method that addresses high time complexity and the interaction between features in classification problems. The proposed method optimizes the number of selected features during evolution and incorporates a conditional probability scheme to detect correlated features, enhancing classification performance. Experimental results demonstrate the method

Author

Piyasha Bhattacharjee

Language

EN