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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: Cell Rep. 2023 Dec 29;43(1):113597. doi: 10.1016/j.celrep.2023.113597

Figure 5. Linear models performed on par with nonlinear machine learning models in neuroimaging-based phenotype prediction.

Figure 5.

We found no consistent evidence of exploitable predictive nonlinear structure in neuroimaging data. Only for DWI-based prediction of sex and age at large (>16,000) training sample sizes did nonlinear models marginally outperform their linear counterparts. Pictured are results for linear and RBF-kernelized nonlinear ridge regression. For other nonlinear machine learning models, see the supplemental information. Error bars indicate SEM.