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cs.LG2022
Comparing Feature Importance and Rule Extraction for Interpretability on Text Data
Gianluigi Lopardo, Damien Garreau
Complex machine learning algorithms are used more and more often in critical tasks involving text data, leading to the development of interpretability methods. Among local methods,…
cs.LG2021
SMACE: A New Method for the Interpretability of Composite Decision Systems
Gianluigi Lopardo, Damien Garreau, Frederic Precioso +1
Interpretability is a pressing issue for decision systems. Many post hoc methods have been proposed to explain the predictions of a single machine learning model. However, business…