Decision tree learning
Decision tree classifiers are attractive models if we care about interpretability. Like the name decision tree suggests, we can think of this model as breaking down our data by making decisions based on asking a series of questions.
Let's consider the following example where we use a decision tree to decide upon an activity on a particular day:
Based on the features in our training set, the decision tree model learns a series of questions to infer the class labels of the samples. Although the preceding figure illustrated the concept of a decision tree based on categorical variables, the same concept applies if our features ...
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