Why do Decision Trees struggle with linear relationships?

Decision Trees approximate linear relationships using step-wise splits, which can be inefficient and fragmented.

Linear relationships require smooth transitions, but Decision Trees create axis-aligned splits. To approximate a diagonal decision boundary, many splits are needed, resulting in deep and complex trees. This increases variance and reduces interpretability compared to linear models.