Consider again the data on used cars (ToyotaCorolla.xls) with 1436 records and details on 38 attributes, including Price, Age, KM, HP, and other specifications. The goal is to predict the price of a used Toyota Corolla based on its specifications.

a. Use XLMiner's neural network routine to fit a model. Depending on XLMiner version, you can probably accept default values for the neural net parameters, except data should be normalized and error tolerance may need to be set to 0 . Record the RMS error for the training data and the validation data. Repeat the process, changing the number of epochs (and only this) to 300,3000 , and 10,000.

i. What happens to the RMS error for the training data as the number of epochs increases?

ii. What happens to the RMS error for the validation data?

iii. Comment on the appropriate number of epochs for the model.