Overview of ML model workflows in pharmaceutical prediction tasks (IMAGE)
Caption
(a) Examples of three major ML model types: tree‐based models (e.g., random forests, gradient boosted trees), kernel‐based models (e.g., support vector machines, Gaussian processes), and deep learning models (e.g., neural networks, graph neural networks), each using molecular descriptors such as logP, pKa, and melting point to predict properties like solubility. (b) Generalized ML pipeline showing stages of data acquisition and cleaning (with features and targets), model evaluation (e.g., regression fitting and performance), and interpretation (e.g., feature importance analysis).
Credit
Rohan Chand Sahu
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