Question: In the context of supervised learning algorithms, the requirement for using a decision tree is that the data be linearly separable. How is it possible

In the context of supervised learning algorithms, the requirement for using a decision tree is that the data be linearly separable. How is it possible to check this in a dataset with several features and what does it mean? Try giving an example of a python code snippet with scikitlearn

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