An Information Entropy Embedding Feature Selection Based on Genetic Algorithm

Abstract

Feature selection is of vital importance to reduce information redundancy and deal with the invalidation of basic classification approaches for massive dataset and too many features. In order to improve the classification accuracy and decrease time complexity, an algorithm with intelligent optimization genetic algorithm and weight distribution based on information entropy is proposed, called EEGA. Information entropy of features is defined as the population labels in GA rather than the direct iteration of individual fitness. Experiments have been performed by using several standard databases with four fitness algorithms. Experimental results have proved that EEGA performs better based on the measure of accuracy. Furthermore, it can significantly reduce the required time when figuring out the better results.

MonDiaL-CAD: Monkeypox diagnosis via selected hybrid CNNs unified with feature selection and ensemble learning

“… 66 The larger the entropy of an attribute, the less information it contains (the more costly the process of entropy decreases) because its appointed weight is lower. To begin calculating the entropy of a feature, the uncertainty function c is described as 67 : where p denotes the related probability. So, the quantification of information entropy E(C) could be noticed by determining the probability of the uncertainty function: where C denotes the collection of all possible events.…”

Retracted: An Information Entropy Embedding Feature Selection Based on Genetic Algorithm

“…Security and Communication Networks has retracted the article titled "An Information Entropy Embedding Feature Selection Based on Genetic Algorithm" [1] due to concerns that the peer review process has been compromised. Following an investigation conducted by the Hindawi Research Integrity team [2], signifcant concerns were identifed with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.…”