What are oblique decision trees?

Oblique decision trees use linear combinations of features instead of axis-aligned splits.

Unlike standard trees that split using a single feature threshold, oblique trees use hyperplanes defined by weighted combinations of features. This allows them to capture complex decision boundaries with fewer splits. However, they are harder to train and interpret due to optimization complexity.