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My previous question was about looking for pseudocodes for Boosting algorithms like XGB, Random Forests and LGBM.

I figured it would be better if i had some resources to refer to, which would detail the internal working of such algorithms.

I feel it would help out a beginner like me in understand the 'under-the-hood' stuff.

If anyone is aware of any relevant resources, especially those which are beginner-friendly, please kindly cite them in your answers.

The answers would be helpful to other beginners too, in the future

Muhammad Yasir
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  • LGBM and xgboost are different software implementations of the larger class of methods called gradient-boosted trees; see [tag:boosting]. Reading a high-quality textbook on machine learning will give you a solid foundation of understanding. *Elements of Statistical Learning* is a good choice. – Sycorax May 22 '20 at 00:54
  • @SycoraxsaysReinstateMonica thanks. can you state the name of the author of the said book or maybe ISBN ? there could be books with similar names, so would highly appreciate it ! – Muhammad Yasir May 23 '20 at 02:13
  • This is the book's website. https://web.stanford.edu/~hastie/ElemStatLearn/ It's available for free. – Sycorax May 23 '20 at 15:06
  • thank you ! much appreciated ! – Muhammad Yasir May 25 '20 at 14:57

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