6. Which of the following can we use to solve the problem of “overfitting” in a neural network?我們可以使用以下哪項解決神經網路中的「過度擬合」問題？Regularization 正則項／懲罰項Activation function 激勵函數Epoch 訓練次數All of the above options 以上選項皆可

A common technique to reduce overfitting in neural networks is to apply ______________, which randomly drops units from the neural network during training.

Which of the following is a technique for preventing overfitting in a supervised learning model?Review LaterAdding more hidden layers to a neural networkIncreasing the learning rate of a modelRegularizationUsing a larger batch size during training

Question 3What is overfitting in machine learning?a) Overfitting occurs when a model has high complexity and captures both information and noise in the training data.b) Overfitting occurs when a model has poor performance on the training data.c) Overfitting is indicated when a model has good performance on the training dataset but relatively poor performance on the testing dataset.d) Overfitting occurs when a model has good performance on the test data.Answer choicesSelect only one optionREVISITa onlya & da & ca, c & d

why regularisation improve overfitting

Which technique can help reduce overfitting in machine learning models? Increasing model complexity Decreasing the amount of training data Regularization Ignoring feature importance