Maximal Uncorrelated Multinomial Logistic Regression
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DOI: 10.1109/access.2019.2921820
Abstract: Multinomial logistic regression (MLR) has been widely used in the field of face recognition, text classification, and so on. However, the standard multinomial logistic regression has not yet stressed the problem of data redundancy. That… read more here.
Keywords: logistic regression; maximal uncorrelated; data redundancy; multinomial logistic ... See more keywords
Data Redundancy Mitigation in V2X Based Collective Perceptions
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DOI: 10.1109/access.2020.2965552
Abstract: Collective perception is a new paradigm to extend the limited horizon of individual vehicles. Incorporating with the recent vehicle-2-x (V2X) technology, connected and autonomous vehicles (CAVs) can periodically share their sensory information, given that traffic… read more here.
Keywords: mitigation v2x; redundancy; data redundancy; redundancy mitigation ... See more keywords
Reliability of Machine Learning in Eliminating Data Redundancy of Radiomics and Reflecting Pathophysiology in COVID-19 Pneumonia: Impact of CT Reconstruction Kernels on Accuracy
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DOI: 10.1109/access.2022.3211080
Abstract: Background: Radiomical data are redundant but they might serve as a tool for lung quantitative assessment reflecting disease severity and actual physiological status of COVID-19 patients. Objective: Test the effectiveness of machine learning in eliminating… read more here.
Keywords: machine; machine learning; data redundancy; learning eliminating ... See more keywords