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Found 3 papers, 1 papers with code
Mixture of Decision Trees for Interpretable Machine Learning
This work introduces a novel interpretable machine learning method called Mixture of Decision Trees (MoDT).
Towards Measuring Bias in Image Classification
For this purpose, first an artificial dataset with a known bias is created and used to train intentionally biased CNNs.
Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization
One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability.
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