Fig. 2: Flow chart of ensemble model structure. | Communications Biology

Fig. 2: Flow chart of ensemble model structure.

From: Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations

Fig. 2

The model relies on jointly training the LASSO and XGBoost model to identify the optimal value for the L1 regularization parameter and the number of boosting steps. CV indicates cross-validation, α refers to the regularization parameter, and Ɵ is the number of boosted trees for XGBoost. The optimal values for these hyperparameters were selected using threefold CV for the mean squared error of the XGBoost model.

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