Density Estimation using Series Expansion
Last "non-parametric" technique (although very parametric)
Write $ p(x) = sum(cj*fj(x)) $ where {$ fj's $} are pre-determined class of functions $ =sum(cj*fj(x)) $
Monomials. E.g. Taylor expansion about Xo in 1-D.
Decision Trees
Reference DHS Chapter 8 Decision tree is one of the most powerful method for classification, because it simplifies the classification by dividing the problem into subproblems. A sample decision tree can be given as follows:
Instead of asking a complicated question $ g(x) >= 0 or <0 $
The idea: Ask a series of simple questions following a tree structure (linear 1-D).