Q8. [2 points) In step 3 of the general approach in page 27, you could either choose the model (trained on the 70% training data) that did the best on the development data, or you could choose the hyper-parameter settings that did best and retrain the model on the 80% union of training and development data. Is either of these options obviously better or worse? Why? LIMITS OF LEARNING 27 hyperparameters. The general approach is as follows: 1. Split your data into 70% training data, 10% development data and 20% test data. 2. For each possible setting of your hyperparameters: (a) Train a model using that setting of hyperparameters on the training data. (b) Compute this model's error rate on the development data. 3. From the above collection of models, choose the one that achieved the lowest error rate on development data. 4. Evaluate that model on the test data to estimate future test perfor- mance. In step 3, you could either choose the model (trained on the 70% train