About this document
Decision Tree Implementation Overview by Omar Ashinawy is a document available to read on EtoBox.
The document describes an implementation of a decision tree algorithm for a course project. It discusses key aspects of the implementation including: - Using information gain to select the best attributes to split the data on at each node. Information gain is calculated using entropy, which measures the purity of a data group. - The decision tree is represented using TreeNode objects, with each node splitting the data based on a attribute value and branching to child nodes. - The implementation makes a
- Author
- Omar Ashinawy
- Language
- EN