High‐dimensional QSAR classification model for anti‐hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge penalty
作者： Zakariya Yahya Algamal , Muhammad Hisyam Lee , Abdo M. Al-Fakih , Madzlan Aziz
DOI: 10.1002/CEM.2889
关键词: Thiourea 、 Logistic regression 、 Anti hepatitis c virus 、 Artificial intelligence 、 Sparse methods 、 Selection (genetic algorithm) 、 Quantitative structure–activity relationship 、 Model interpretation 、 High dimensional 、 Mathematics 、 Pattern recognition
摘要: This study addresses the problem of high-dimensionality quantitative structure-activity relationship (QSAR) classification modeling. A new selection descriptors that truly affect biological activity and a QSAR model estimation method are proposed by combining sparse logistic regression with bridge penalty for classifying anti-hepatitis C virus thiourea derivatives. Compared to other commonly used methods, shows superior results in terms accuracy interpretation.
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