#decision-trees

#decision-trees

Chess gameplay can be analyzed as a decision tree to identify tipping points that significantly affect match outcomes.

Decision trees help streamline UI design decisions and prevent never-ending discussions.

Decision trees are a popular machine learning model because of their simplicity and interpretability.

Key components of decision tree construction include the root node, internal nodes, leaf nodes, decision or split rule, branches, parent and child nodes, and depth.