Which of the following statements is or are true regarding regularisation?多项选择题

题目图片
A

Regularisation is a form of empirical risk minimisation.

B

Regularisation focuses on minimising the training error over everything else.

C

Regularisation is not necessary for neural networks because they have too many parameters.

D

Lasso and ridge regression add an additional function to be minimised during the training process, which represents the complexity of the model.

E

Regularisation attempts to minimise overfitting by finding a trade-off between predictive power and model simplicity.

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