Forest GUMP: a tool for verification and explanation

Abstract

In this paper, we present Forest GUMP (for Generalized, Unifying Merge Process) a tool for verification and precise explanation of Random forests. Besides pre/post-condition-based verification and equivalence checking, Forest GUMP also supports three concepts of explanation, the well-known model explanation and outcome explanation, as well as class characterization, i.e., the precise characterization of all samples that are equally classified. Key technology to achieve these results is algebraic aggregation, i.e., the transformation of a Random Forest into a semantically equivalent, concise white-box representation in terms of Algebraic Decision Diagrams (ADDs). The paper sketches the method and demonstrates the use of Forest GUMP along illustrative examples. This way readers should acquire an intuition about the tool, and the way how it should be used to increase the understanding not only of the considered dataset, but also of the character of Random Forests and the ADD technology, here enriched to comprise infeasible path elimination. As Forest GUMP is publicly available all experiments can be reproduced, modified, and complemented using any dataset that is available in the ARFF format.