10 - 704 : Information Processing and Learning Spring 2015 Lecture 6 : January 29
نویسنده
چکیده
Last time we discussed the Chow-Liu algorithm, which uses mutual information estimation to learn the best tree graphical model representing data. Recall that, in each iteration, the Chow-Liu algorithm greedily adds an edge between the pair of unconnected variables exhibiting the greatest (estimated) mutual information. Because we only add edges between unconnected variables, (unconditional) mutual information suffices. However, to learn general graphical models (allowing multiple paths between nodes), we need measure conditional dependence, for which we can estimate conditional mutual information.
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