Figure 4

Predicting worm age using machine learning. The activities of genes or subnetworks (subnetwork activity is calculated as the mean activity of its member genes) are used by support vector regression (SVR) algorithms to predict age on the basis of gene expression. Performance is typically measured using both the mean-squared error (MSE) of the difference between true and predicted ages, and the squared correlation coefficient between true and predicted ages.