#concept-drift

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In which training situation is the objective non-stationary?

A fraud detector is retrained continually while fraudsters keep changing tactics1
An image classifier is trained for many epochs on a fixed dataset, shuffled anew every epoch2
A network is trained on a fixed dataset whose loss surface has many local minima3
The learning rate of a model trained on a fixed dataset is halved every ten epochs4

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