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In a problem with limited data where you want to prevent the model from overfitting to the training data, which of the following is the most appropriate effective countermeasure?
①Increase the number of layers and parameters of the network.
②Significantly increase the learning rate.
③Introduce a regularization term (L1, L2, etc.)
④Remove part of the training data.
⑤Add a large number of features to make the model more complex.