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Classification with Decision Trees

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Overview

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This course explains how to implement classification with decision trees in R. It covers tree-based models, a gold loan case study, CART, Gini index, entropy, misclassification error, impurity measurement, and decision tree algorithm types.

Syllabus

➤ Skip Intro: .
Introduction.
What is Classification?.
What is Decision Tree Learning?.
Advantages of using Tree-based Models.
Gold Loan Case Study.
Decision Tree in-depth Concept.
Gini Index, Entropy, Misclassification Error.
Measuring Impurity.
Types of Decision Tree algorithms.

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