Fig. 1.

Supervised learning for predicting cancer-related phenotypes from gene expression data. a Classification identifies target labels, including cancer subtypes; b regression can predict progression and outcome measures, such as disease-free intervals. After the data is partitioned into training and test sets, a ML algorithm is fit on the training data. The model is evaluated using hold-out test data