Minimum description length

The minimum description length (MDL) principle formalizes Occam's razor by selecting the model that minimizes the total bits needed to encode both the model and the data. Developed by Jorma Rissanen, MDL treats model selection as a compression problem. A good model compresses the data well; a bad model requires many bits. MDL shares asymptotic properties with the BIC but avoids prior distributions. It extends to stochastic complexity for non-parametric settings.