Joey Joystick is a computer programmer. While he was in his final year of university studies,
he worked as an intern with a local electronic games producer, Great Games Pty Ltd. Joey
impressed his supervisors with his insightful comments and other input on design work. They
were so impressed with his work on one design, Crypt Force, that they gave him part credit
for it and paid him a general bonus for it. Crypt Force ultimately won an industry award and
proved to be a big seller for the company.
After Joey’s university graduation ceremony, he was ushered aside by a Great Games
executive who showed him a document and said:
“We’re very impressed by your work, Joey. We’d like you to join us permanently—
we’re sure you’ll be happy with the deal we can offer you.”
The document was a contract of employment which contained the following clauses:
1. The duration of the contract is three (3) years.
9. The employee (Joey) agrees that he will not for the duration of the employment
contract or for a period of one year after the conclusion of the employment
undertake design activities in Australia for the purposes of the production of
electronic games or any other form of entertainment.
Neural Net Evolution. A neural net typically starts out with random weights; hence it produces essentially random predictions in the first iteration. Describe how the neural net evolves (in JMP) to produce a more accurate prediction? Car Sales. Consider again the data on used cars ( ) 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. Determine which variables to include, and use the neural platform in JMP Pro to fit a model. Use the validation column for validation, and use the default values in the Neural model launch dialog. Record the RMSE for the training data and the validation data, and save the formula for the model to the data table (use the Save Fast Formulas option, which will save the formula as one column in the data table). Repeat the process, changing the number of nodes (and ouly this) to 5, 10, and 25. i. Using your recorded values, what happens to the RMSE for the training data as the number of nodes increases? ii. What happens to the RMSE for the validation data? iii. Comment on the appropriate number of nodes for the model. iv. Use the Model Comparison platform to compare these four models (use the Validation column as either aByvariable or as a Group variable, and focus only on the validation data). Here, RASE is reported rather than RMSE. Compare RASE and AAE (average absolute error) values for these four models. Which model has the lowest “error”? b. Conduct a sintilar experiment to assess the effect of changing the number oflayers in the network as well as the activation functions.
July 30, 2021
7:22 pm
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