Ridge regression baseline model outperforms deep learning method for cancer genetic dependency prediction

Chang, D.; Zhang, X.

doi:10.1101/2023.11.29.569083

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bioRxiv · 10.1101/2023.11.29.569083

Ridge regression baseline model outperforms deep learning method for cancer genetic dependency prediction

Chang, D.·Zhang, X.

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Abstract

Accurately predicting genetic or other cellular vulnerabilities of unscreened, or difficult to screen, cancer samples will allow vast advancements in precision oncology. We re-analyzed a recently published deep learning method for predicting cancer genetic dependencies from their omics profiles. After implementing a ridge regression baseline model with an alternative, simplified problem setup, we achieved a model that outperforms the original deep learning method. Our study demonstrates the importance of problem formulation in machine learning applications and underscores the need for rigorous comparisons with baseline approaches.

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Chang, D., Zhang, X.. 2023-12-01. Ridge regression baseline model outperforms deep learning method for cancer genetic dependency prediction. https://doi.org/10.1101/2023.11.29.569083

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