20.04.2022

MCML Researchers With One Paper at AISTATS 2022
25th International Conference on Artificial Intelligence and Statistic (AISTATS 2022). Virtual, 25.04.2022–27.04.2022
We are happy to announce that MCML researchers are represented with one paper at AISTATS 2022. Congrats to our researchers!
REPID: Regional Effect Plots with implicit Interaction Detection.
AISTATS 2022 - 25th International Conference on Artificial Intelligence and Statistics. Virtual, Mar 28-30, 2022. URL
Abstract
Machine learning models can automatically learn complex relationships, such as non-linear and interaction effects. Interpretable machine learning methods such as partial dependence plots visualize marginal feature effects but may lead to misleading interpretations when feature interactions are present. Hence, employing additional methods that can detect and measure the strength of interactions is paramount to better understand the inner workings of machine learning models. We demonstrate several drawbacks of existing global interaction detection approaches, characterize them theoretically, and evaluate them empirically. Furthermore, we introduce regional effect plots with implicit interaction detection, a novel framework to detect interactions between a feature of interest and other features. The framework also quantifies the strength of interactions and provides interpretable and distinct regions in which feature effects can be interpreted more reliably, as they are less confounded by interactions. We prove the theoretical eligibility of our method and show its applicability on various simulation and real-world examples.
MCML Authors

Julia Herbinger
Dr.
* Former Member
Statistical Learning and Data Science
Statistical Learning and Data Science
20.04.2022
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