Which of the following strategies are commonly used to diagnose overfitting in neural networks?

Options:

$1)$ Evaluating the model's performance with different subsets of features.

$2)$ Visualizing the learning curves for training and validation losses.

$3)$ Monitoring the model's performance on both training and validation datasets.

$4)$ Checking if the training loss is significantly lower than the validation loss.

$5)$ Increasing the complexity of the model to match the training error.