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Information Gain at decision trees

When making decision trees, two different methods are used to find the best feature to split a dataset on: Gini impurity and Information Gain. An intuitive interpretation of Information Gain is that it is a measure of how much information the individual features provide us about the different classes.

Decision Trees
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