Random forest from R vs Python Scikit Learn

I wanted to ask why did we use the Random Forest algorithm from R compared to Python Scikit Learn . I looked online for answers and it says that the python random forest is both more accurate and also much faster . So i am confused on why it is the reason for using it ?

Hi @omarElta ,

I believe there might be some functional differences between R and Python when it comes to the Random Forest algorithm.
However, in terms of data analysis, the choice of framework is not a major issue, I believe the important point should be on performing the validation correctly.

Of course, each programming language has its own merits and demerits, and it would be beneficial to make a choice after considering these.

For instance, R is a language specifically designed for statistical analysis and data analysis, equipped with advanced packages and features.
On the other hand, Python not only provides libraries and frameworks for data analysis and machine learning but also is a general-purpose programming language that can be used for diverse applications, including web development, making it easier to collaborate with other domains.

I hope you find this helpful.

Best regards,

Hello @omarElta
Thanks a lot for posting your question on discourse. I would strongly suggest you to view this website which contains 2 books about statistical learning in R and Python. You can search for the word “Random Forest” in the books and find further information about the implementation differences of Random Forest in R and Python. https://www.statlearning.com/

Just an add on to Nakamura’s post. I hope you like the books!
Can Koz

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