Learning max-weight discriminative forests
Learning max-weight discriminative forests
We present a method for sequential learning of increasingly complex graphical models for discriminating between two hypotheses. We generate forests for each hypothesis, each with no more edges than a spanning tree, which optimize an information-theoretic criteria. The method relies on a straightforward extension of the efficient max-weight spanning tree …