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Ryan Orban

Ryan Orban

Subject
2 entries

Decision Theory

Bookmarks

  1. Probable Points and Credible Intervals: Bayesian Decision Theory

    Part 2 of Rasmus Baath's gentle intro to Bayesian decision theory — covering how credible intervals and probable points are used to make decisions under uncertainty. One of the cleaner elementary treatments of the Bayesian decision framework.

  2. The Geometry of Classifiers

    Nina Zumel's geometric treatment of machine learning classifiers — how decision boundaries, margins, and probability regions look in feature space. Builds visual intuition for why different classifier families make the tradeoffs they do.

All bookmarks