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A sparse QSRR model for predicting retention indices of essential oils based on robust screening approach

A robust screening approach and a sparse quantitative structure–retention relationship (QSRR) model for predicting retention indices (RIs) of 169 constituents of essential oils is proposed. The proposed approach is represented in two steps. First, dimension reduction was performed using the proposed...

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書誌詳細
主要な著者:	Al Fakih, A. M., Algamal, Z. Y., Lee, M. H., Aziz, M.
フォーマット:	論文
出版事項:	Taylor and Francis Ltd. 2017
主題:	QD Chemistry
オンライン･アクセス:	http://eprints.utm.my/id/eprint/75754/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030458483&doi=10.1080%2f1062936X.2017.1375010&partnerID=40&md5=47d22807f6a4795a52fa1244310bb90b
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