Difference between revisions of "Exam 2 Study Guide"
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(Created page with "Exam 2 will consist of approximately 3 multiple choice questions on each topic listed below: * Comparison of different regression learner performance characteristics: Trees,...") |
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* Things you should know because you did the projects. In sample versus out of sample. Istanbul problem, why did shuffling help? | * Things you should know because you did the projects. In sample versus out of sample. Istanbul problem, why did shuffling help? | ||
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| + | The exam will include 30 questions. You will have 30 minutes (plus 5 extra in case of a problem) to complete the exam. The exam is closed book, closed notes. You can use an on screen calculator. | ||
Revision as of 20:08, 17 July 2017
Exam 2 will consist of approximately 3 multiple choice questions on each topic listed below:
- Comparison of different regression learner performance characteristics: Trees, forests, KNN, linreg
- Comparison of learner types: Regression, Classification, RL
- Overfitting: Definition, how to identify, what might prevent it, what might cause it?
- Bootstrap aggregating.
- Boosting.
- Decision trees. Random versus information based construction. Advantages of one over the other.
- Reinforcement learning: How is it defined? Questions about State, Action, Transitions, Reward
- Q-Learning. The update equation, definition of Q
- Dyna-Q
- Things you should know because you did the projects. In sample versus out of sample. Istanbul problem, why did shuffling help?
- Options
The exam will include 30 questions. You will have 30 minutes (plus 5 extra in case of a problem) to complete the exam. The exam is closed book, closed notes. You can use an on screen calculator.
