Machine learning is a broad branch of data science. Also referred to as statistical learning. Includes [[supervised learning]], [[unsupervised learning]], and [[reinforcement learning]]. Machine learning tasks include model evaluation and model selection. Read the latest in [Papers With Code](https://paperswithcode.com/) ## model evaluation - holdout - [[k-fold cross-validation]] - [[bootstrap]] confusion matrix sensitivity, specificity, precision, accuracy, F1 ROC, AUC-ROC ## model selection (mean/relative) absolute error (mean/relative) square error t-test for model selection $t = \frac{\bar {err}(M_1) - \bar {err} (M_2)}{\sqrt{var(M_1 - M_2)/k}}$ degrees of freedom is $k-1$ in [[k-fold cross-validation]].