The Minimum Description Length Principle - (Adaptive Computation and Machine Learning) by Peter D Grunwald (Paperback)

The MDL Principle is a powerful method of inductive inference that has far-reaching implications in various fields, including statistics, pattern classification, machine learning, data mining, biology, econometrics, and experimental psychology.

This comprehensive guide provides an accessible introduction to the MDL Principle, offering a step-by-step explanation of its conceptual issues and practical applications.

With its emphasis on model selection, prediction, and estimation problems, the MDL Principle is particularly well-suited for dealing with complex models that can easily overfit the data.

This reference guide is an essential resource for graduate students, researchers, and professionals in related fields who seek to harness the power of the MDL Principle in their work.