High-dimensional QSAR modelling using penalized linear regression model with L1/2-norm

High-dimensional QSAR modelling using penalized linear regression model with L1/2-norm

In high-dimensional quantitative structure–activity relationship (QSAR) modelling, penalization methods have been a popular choice to simultaneously address molecular descriptor selection and QSAR model estimation. In this study, a penalized linear regression model with L1/2-norm is proposed. Furthe...

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Bibliographic Details
Main Authors: Algamal, Z. Y., Lee, M. H., Al-Fakih, A. M., Aziz, M.
Format: Article
Published: Taylor and Francis Ltd. 2016
Subjects:
QD Chemistry
Online Access:http://eprints.utm.my/id/eprint/72108/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987643691&doi=10.1080%2f1062936X.2016.1228696&partnerID=40&md5=4d4834740f41f51ed40fd692c7811449
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Institution: Universiti Teknologi Malaysia

Internet

http://eprints.utm.my/id/eprint/72108/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987643691&doi=10.1080%2f1062936X.2016.1228696&partnerID=40&md5=4d4834740f41f51ed40fd692c7811449

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