anonymous12 comments on How An Algorithm Feels From Inside - Less Wrong

87 Post author: Eliezer_Yudkowsky 11 February 2008 02:35AM

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Comment author: anonymous12 11 February 2008 08:57:24PM 4 points [-]

Silas, see Naive Bayes classifier for how an "observable characteristics graph" similar to Network 2 should work in theory. It's not clear whether Hopfield or Hebbian learning can implement this, though.

To put it simply, Network 2 makes the strong assumption that the only influence on features such as color or shape is whether the object is a a rube or a blegg. This is an extremely strong assumption which is often inaccurate; despite this, naive Bayes classifiers work extremely well in practice.