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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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Taylor and Francis Ltd.
2016
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| Subjects: | |
| 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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