Decision Tree
Explore how decision trees work as intuitive, supervised learning models for classification and regression tasks. Understand their structure, splitting criteria with Gini impurity, and practical implementation using scikit-learn. Gain insights into model training, evaluation with confusion matrices, and visualization for clear interpretability.
We'll cover the following...
What is Decision Tree
A Decision Tree is a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal. They are also a ...