Fig. 2
From: Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes
Predictive correlation (left panel) and mean squared error of prediction (right panel) of two conventional statistical methods (GBLUP and Bayes B) and four machine-learning methods including random forests (RF), gradient boosting (Boosting), multilayer perceptron (MLP) and convolutional neural network (CNN) using a real dataset of sire conception rate records from US Holstein bulls. The whiskers represent 95% confidence intervals