How decision trees are trained 🌲 ↦
A simple explanation of Gini Impurity and how it’s used to train decision trees. In brief:
Gini Impurity is the probability of incorrectly classifying a randomly chosen element in the dataset if it were randomly labeled according to the class distribution in the dataset
Click through for the full break down and some helpful examples.
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