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A reliable selection of a representative subset of chemical compounds has been reported to be crucial for numerous tasks in computational chemistry and chemoinformatics. We investigated the usability of an approach on the basis of the k‐medoid algorithm for this task and in particular for experimental design and the split between training and validation set. We therefore compared the performance of...
The accuracy of in silico models can be inhomogeneous: models can show excellent performance on some chemical subspaces but have low accuracy on others. We show that applicability domain (AD) approaches can differentiate reliable and non‐reliable predictions and identify those with experimental accuracy for both regression and classification models. For reliably predicted molecules, the predicted...
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