Prediction of the Aqueous Solubility of Compounds Based on Light Gradient Boosting Machines with Molecular Fingerprints and the Cuckoo Search Algorithm
Mengshan Li, Huijie Chen, Hang Zhang, Ming Zeng, Bingsheng Chen, Lixin Guan
Abstract
of the CS-LightGBM model were, respectively, 0.7785, 0.5117, and 0.8575. In addition, this model has good scalability and can be used to solve solubility prediction problems in other fields such as solvent selection and drug screening.
Topics & Concepts
SolubilityGradient boostingMachine learningArtificial intelligenceCuckoo searchComputer scienceAlgorithmBoosting (machine learning)HyperparameterChemistryRandom forestParticle swarm optimizationOrganic chemistryComputational Drug Discovery MethodsAnalytical Chemistry and ChromatographyMachine Learning in Materials Science