Real-world uses

Created for this library

1. 1.

   A telco churn team prefers axis-aligned conditions in its decision tree because business reviewers can read each split as a single feature threshold.

2. 2.

   A risk modeling team trains a gradient boosted tree with axis-aligned conditions so each split is easy to translate into a policy rule.

3. 3.

   A pricing analytics team uses axis-aligned conditions in its segmentation tree so the marketing team can describe each segment in plain language.