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Estimation and Interpretation of Machine Learning Models with Customized Surrogate Model
2021
Electronics
Machine learning has the potential to predict unseen data and thus improve the productivity and processes of daily life activities. Notwithstanding its adaptiveness, several sensitive applications based on such technology cannot compromise our trust in them; thus, highly accurate machine learning models require reason. Such models are black boxes for end-users. Therefore, the concept of interpretability plays the role if assisting users in a couple of ways. Interpretable models are models that
doi:10.3390/electronics10233045
fatcat:vmm2ju7pizf4pcky2kyt3lc7lu