Hi Aditya,
It's hard for us to answer without any specific question. Perhaps this
will help:
https://scikit-learn.org/stable/developers/contributing.html#reading-the-existing-code-base
The tree code is quite complex, because it is very generic and can
support many different settings (multioutput, sparse data, etc) as well
as many different parameters like max_features, splitter, presort... I
would suggest being familiar with the different parameters before diving
into the code.
Nicolas
On 1/14/20 6:00 AM, aditya aggarwal wrote:
Hello
I am trying to understand the order of functions call for performing
classification using decision tree in sklearn. I need to make and test
some changes in the algorithm used to calculate best split for my
dissertation. I have looked up the documentation available of sklearn
and other sources available online but couldn't seem to crack it. Any
help would be appreciated.
Thanks
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