While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...

Currently employed strategies for their improved detection include the prolongation of the detection windows for exogenous AAS, non-targeted and indirect analytical approaches for the detection of ...

By leveraging supervised learning algorithms like Logistic Regression, SVM, and Multinomial Naïve Bayes ... The goal is to create a scalable, reliable fake news detection system that can empower users ...

In this paper, we proposed a framework, called Mulr4FL, for fault localization using a multivariate logistic regression model that combined both static and dynamic features collected from the program ...

Abstract: The Maximus, bootstrap, and Bayes methods can be useful in calculating lower s-confidence limits on system reliability using binomial component test data. The bootstrap and Bayes methods use ...

Key Laboratory of Optic-electric Sensing and Analytical Chemistry for Life Science, Ministry of Education, Shandong Key Laboratory of Biochemical Analysis, Key Laboratory of Analytical Chemistry for ...

To make ALS applicable to logistic regression, we introduce an auxiliary function derived from Pólya-Gamma augmentation, allowing logistic loss to be minimized as a weighted squared loss. We apply the ...