Which technique serves as a form of regularization by restricting the exploration of parameter space from the initial parameters, and requires validation data to determine its timing?*a) Lasso regressionb) Dropoutc) Early stoppingd) Ridge regression

The answer is c) Early stopping. This technique serves as a form of regularization by restricting the exploration of parameter space from the initial parameters, and requires validation data to determine its timing. Early stopping works by stopping the training process before the model starts to overfit. This is usually determined by monitoring the error on a separate validation dataset and stopping training when the error starts to increase.

The correct answer is c) Early stopping. This technique serves as a form of regularization by restricting the exploration of parameter space from the initial parameters, and requires validation data to determine its timing. Early stopping works by stopping the training process before the model starts to overfit. This is usually determined by monitoring the error on a validation set during the training process, where the training is stopped when the error on the validation set starts to increase.