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Found 3 papers, 2 papers with code
Computationally Efficient Feature Significance and Importance for Machine Learning Models
We develop a simple and computationally efficient significance test for the features of a machine learning model.
Significance Tests for Neural Networks
We develop a pivotal test to assess the statistical significance of the feature variables in a single-layer feedforward neural network regression model.
Sensitivity based Neural Networks Explanations
Although neural networks can achieve very high predictive performance on various different tasks such as image recognition or natural language processing, they are often considered as opaque "black boxes".
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