>[!abstract] >Minimum Description Length (MDL) is a model selection principle where the shortest description of the data is the best model. MDL methods learn through a data compression perspective and are sometimes described as mathematical applications of Occam's razor. The MDL principle can be extended to other forms of inductive inference and learning, for example to estimation and sequential prediction, without explicitly identifying a single model of the data (Wikipedia, 2025). >[!related] >- **North** (upstream): [[Kolmogorov complexity]] >- **West** (similar): — >- **East** (different): — >- **South** (downstream): —