C5.0 decision tree algorithm implementation request

[MartinMarzi]

Hi,

it would be very helpful to have a C5.0 Decision tree algorithm implementation in tfdf as there is none until now for Python and guess there is quite some demand to have this well know and one of the best algorithms at hand in Python!

It is quite different to CART: -multiple branches,

• Information Gain (Entropy) as its splitting criteria,
• different pruning technique (Binomial Confidence Limit)
• different handling of missing values (estimate missing values as a function of other attributes or apportions the case statistically among the results)

I am sure it would boost the recognition and usability of tfdf library and make it especially useful for when strong and simple models that are directly explainable are needed.

Thank you for taking note!

[MartinMarzi]

If easier to implement C4.5 would be great as well. Many thanks.