NLS: an accurate and yet easy-to-interpret regression method

Understand

An important feature of successful supervised machine learning applications is to be able to explain the predictions given by the regression or classification model being used.

• However, most state-of-the-art models that have good predictive power lead to predictions that are hard to interpret.
• Thus, several model-agnostic interpreters have been developed recently as a way of explaining black-box classifiers.
• In practice, using these methods is a slow process because a novel fitting is required for each new testing instance, and several non-trivial choices must be made.