We are happy to report our tool: Nirdizati Light: A Modular Framework for Explainable Predictive Process Monitoring, has been accepted at the Demo & Resources track for BPM 202
Authors: Andrei Buliga, Riccardo Graziosi, Chiara Di Francescomarino, Chiara Ghidini, Williams Rizzi, Massimiliano Ronzani, Fabrizio Maria Maggi
Abstract: Nirdizati Light is an innovative Python package designed for Explainable Predictive Process Monitoring (XPPM). It addresses the need for a modular, flexible tool to compare predictive models, and generate explanations for the predictions made by the predictive models. By integrating consolidated frameworks libraries for process mining, machine learning, and explainable AI, it offers a comprehensive approach to predictive model construction and explanation generation. This paper discusses the tool’s key features, and its significance in the BPM community.
