I've read in the documentation that sklearn uses CART algorithm for trees.
Are there specific attributes to change so that it becomes similar to a c4.5 implementation?
is it possible to implement c4.5 algorithm in scikit-learn?
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CART and C4.5 are somehow similar algorithms, but there are fundamental differences which won't let you tweak sklearn's implementation to get a C4.5 without a lot of work.
C4.5 uses rule sets to decide where to split the data, whereas CART merely uses a numerical splitting criterion.
You can take a look at this implementation of C4.5