Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization

10 Apr 2019Nina SchaafMarco F. HuberJohannes Maucher

One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability. In this work, a practicable approach of gaining explainability of deep artificial neural networks (NN) using an interpretable surrogate model based on decision trees is presented... (read more)

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