Classification methods with only nominal attributes 
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*I would like to know what classification methods can naturally deal with only nominal attributes. An example is decision trees created by C4.5. I imagine that other classifiers based on decision trees and rule sets can also be used.

*Apart from these kinds of algorithms, are there others that follow different approaches to decision trees or rule sets?


If you use dummy coding you can in principle use most of the standard methods like neural networks, gradient boosting machines (also those which don't use trees as weak learners), kernel methods...
