Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?

Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?

10.1002/cem.3349

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Main Authors: Lovrić, M., Pavlović, K., Žuvela, P., Spataru, Adrian, Lučić, B., Kern, Roman, Wong, Ming Wah
Other Authors: CHEMISTRY
Format: Article
Published: John Wiley and Sons Ltd 2022
Subjects:
consensus modeling
LASSO
LightGBM
PCA
permutation importance
QSAR
random forests
Online Access:https://scholarbank.nus.edu.sg/handle/10635/232224
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Institution: National University of Singapore
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spelling sg-nus-scholar.10635-2322242024-11-09T19:36:30Z Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability? Lovrić, M. Pavlović, K. Žuvela, P. Spataru, Adrian Lučić, B. Kern, Roman Wong, Ming Wah CHEMISTRY consensus modeling LASSO LightGBM PCA permutation importance QSAR random forests 10.1002/cem.3349 Journal of Chemometrics 35 7-8 e3349 2022-10-11T08:08:48Z 2022-10-11T08:08:48Z 2021-05-07 Article Lovrić, M., Pavlović, K., Žuvela, P., Spataru, Adrian, Lučić, B., Kern, Roman, Wong, Ming Wah (2021-05-07). Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?. Journal of Chemometrics 35 (7-8) : e3349. ScholarBank@NUS Repository. https://doi.org/10.1002/cem.3349 0886-9383 https://scholarbank.nus.edu.sg/handle/10635/232224 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ John Wiley and Sons Ltd Scopus OA2021
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
topic consensus modeling
LASSO
LightGBM
PCA
permutation importance
QSAR
random forests
spellingShingle consensus modeling
LASSO
LightGBM
PCA
permutation importance
QSAR
random forests
Lovrić, M.
Pavlović, K.
Žuvela, P.
Spataru, Adrian
Lučić, B.
Kern, Roman
Wong, Ming Wah
Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
description 10.1002/cem.3349
author2 CHEMISTRY
author_facet CHEMISTRY
Lovrić, M.
Pavlović, K.
Žuvela, P.
Spataru, Adrian
Lučić, B.
Kern, Roman
Wong, Ming Wah
format Article
author Lovrić, M.
Pavlović, K.
Žuvela, P.
Spataru, Adrian
Lučić, B.
Kern, Roman
Wong, Ming Wah
author_sort Lovrić, M.
title Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
title_short Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
title_full Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
title_fullStr Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
title_full_unstemmed Machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: Generalization, complexity, or predictive ability?
title_sort machine learning in prediction of intrinsic aqueous solubility of drug-like compounds: generalization, complexity, or predictive ability?
publisher John Wiley and Sons Ltd
publishDate 2022
url https://scholarbank.nus.edu.sg/handle/10635/232224
_version_ 1821216548192256000

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