Abstract
Interpretability and predictive performance are important aspects of a machine learning model. Typically, there is a trade-off between interpretability and predictive performance. This trade-off results in a choice between accurate but opaque models such as multilayer perceptron (MLP) and less accurate but more transparent models such as logistic regression (LR).
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