This is a process diagram of how LGBM constructs a decision tree for classification or prediction. The model discretizes the input features and establishes the histogram. Then according to these established histograms, features are selected as nodes to split and build a decision tree. Each decision tree would give a possible result, and the final result will be calculated according to the results of all the decision trees.