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This introductory course explains decision tree learning for classification and regression, including tree structure, splitting criteria, entropy, Gini index, pruning, algorithm comparisons, and a gold-loan attrition case study.
Syllabus
- Introduction to decision tree.
- What is decision tree learning and its types.
- Classification tree learning and important terms.
- Difference between tree model and logistic regression model.
- Decision Tree Case Study: Gold loan attrition problem.
- Career Fields in Analytics.
- Gini index, entropy,.
- Decision tree algorithms.
- Advantages and disadvantages of decision tree.
- Decision tree example.
- Summary.
Taught by
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