说明随机森林（RF）与梯度提升决策树（GBDT）的差异

Decision Tree
Decision tree is a widely used method in machine learning for classification and regression tasks, represented by nodes and directed edges. It represents data through a hierarchical structure based on nodes and their connections. The primary objective is to achieve classification by partitioning the feature space through successive splits. The algorithm involves selecting features during the tree construction phase. Tree generation is followed by pruning to enhance generalization and prevent overfitting. Most decision tree learning algorithms share a similar approach in gen