Random Forest Regression for Drug Solubility Prediction in Cosolvent Media
Published: 23 July 2025| Version 1 | DOI: 10.17632/wd3gv852rw.1
Contributors:
, , Description
This notebook uses a Random Forest Regressor to model drug solubility based on cosolvent system variables. It highlights feature importance, model robustness, and generalization ability.
Files
Steps to reproduce
The dataset DatasetSolubilityDrugV1, used for training the neural network, is available at the following link: https://data.mendeley.com/datasets/g686s23sy5/1. It should be cited as: Delgado, Daniel Ricardo; Vergara, Mateo; Cardenas Torres, Rossember Edén (2025), “Database of drug solubility in cosolvent mixtures at different temperatures.”, Mendeley Data, V1, https://doi.org/10.17632/g686s23sy5.1
Institutions
- Universidad de America
- Universidad Cooperativa de Colombia
Categories
Chemistry, Data Science, Machine Learning, Applied Computer Science