A tutorial showing, through a synthetic hiring example, that covariate shift, sample selection bias, and imbalance bias in training data can be learned by a neural network and visualized interactively.
On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
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Understanding Bias in Machine Learning
A tutorial showing, through a synthetic hiring example, that covariate shift, sample selection bias, and imbalance bias in training data can be learned by a neural network and visualized interactively.