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arXiv · 2001.03207

Split Optimization for Protein/Ligand Binding Models

Brian Davis·Kevin Mcloughlin·Jonathan Allen·Sally Ellingson
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Abstract

In this paper, we investigate potential biases in datasets used to make drug binding predictions using machine learning. We investigate a recently published metric called the Asymmetric Validation Embedding (AVE) bias which is used to quantify this bias and detect overfitting. We compare it to a slightly revised version and introduce a new weighted metric. We find that the new metrics allow to quantify overfitting while not overly limiting training data and produce models with greater predictive value.

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Brian Davis, Kevin Mcloughlin, Jonathan Allen, Sally Ellingson. 2020-01-09. Split Optimization for Protein/Ligand Binding Models. https://arxiv.org/abs/2001.03207

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