WitrynaI've tried to dig in the code of xgboost and found out this method (already cut off irrelevant parts): def get_score (self, fmap='', importance_type='gain'): trees = self.get_dump (fmap, with_stats=True) importance_type += '=' fmap = {} gmap = {} for tree in trees: for line in tree.split ('\n'): # look for the opening square bracket arr = line ... Witryna6 cze 2024 · XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements Machine Learning algorithms under the Gradient Boosting framework. It provides a parallel tree boosting to solve many data science problems in a fast and accurate way. Contributed by: Sreekanth Boosting
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