How Do You Build and Validate 1500 Models and What Can You Learn from Them?

The document describes building and validating over 1,500 machine learning models from datasets in ChEMBL. An automated process ("model factory") was developed using KNIME to build models for each dataset in a reproducible way. The process involved extracting data, transforming structures, learning models, and evaluating performance. While initial validation results were promising, further analysis found models did not generalize well across similar datasets for the same target, indicating overfitting. More work is needed to improve model generalization.