Implement a decision tree : Working of a Decision Tree

The video tutorial explains how decision trees are split using criteria like the Gini index and information gain. It details the calculation of the Gini index to measure homogeneity and how information gain is used to reduce impurity by decreasing entropy. Examples are provided to illustrate these concepts, focusing on selecting criteria for splitting nodes based on attributes like college degree and years of experience.

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