Decision Trees
Explore decision trees as essential models in machine learning to understand classification and regression tasks. Discover how decision trees are built, including key algorithms like ID3, C4.5, and CART, and learn pruning methods to reduce overfitting. Understand how trees split data based on features and how to evaluate model performance efficiently.
Decision Trees
Decision Trees are powerful and provide an output that domain experts and practitioners can easily understand. Decision Trees provide the basis for many Ensemble Methods, which involve using multiple models for inference and producing the output for the datasets at hand.
Decision Tree, as the name suggests, is constructed in a Tree manner, including a root node, internal nodes, and leaf nodes. Leaf nodes, also known ...