As stated in the article Michelle referred you to, XGBoost is not an algorithm, just an efficient implementation of gradient boosting in Python. MATLAB supports gradient boosting, and since R2019b we also support the binning that makes XGBoost very efficient. You activate the binning with the NumBins name-value parameter to the fit*ensemble functions.
Hi Redha, unfortunately I didn't find any matlab implementation of xgboost so far. But I'm replacing it with the "Method" "AdaBoostM1" that you can find here: https://www.mathworks.com/help/stats/fitcensemble.html#namevaluepairarguments In my tests matlab adaptive boost is outperforming R xgboost in almost any scenario so I'm pretty satisfied. Give it a try!
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5563301/ talks about preprocessing in MATLAB and about using Python scikit libraries for xgboost. It does not actually state that they call Python from MATLAB but that approach would sound plausible.
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