Decision Tree is a kind of supervised learning technique that may be used for each classification and Regression issue, however principally it’s most popular for determination Classification issues. it’s a tree-structured classifier, wherever internal nodes represent the options of a dataset, branches represent the selection rules and each leaf node represents the result.
Want to know more about the introduction to Decision Tree Algorithm? Read the blog post at https://k21academy.com/aiml16 to learn more.
The blog post covers:
1. Decision Tree
2. Why use Decision Tree
3. Decision Tree Terminologies
4. How Decision Tree Algorithm works
7. Real-Life Example
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