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ECM3420 Learning from Data
Answer ALL questions.
Please use EXAM ANSWER SHEET for writing your answers.
The marks for this module are calculated from 60% of the percentage mark for this paper plus 40% of the percentage mark for associated coursework.
This is an Open Book exam
Section 1: Multiple Choice Questions
There are two types of questions:
1- What methods could be used to help reduce overfitting in decision trees? [Select all the correct statements].
☐ A) Pruning.
☐ B) Enforce a minimum number of samples in leaf nodes.
☐ C) Make sure that each leaf-node is one pure class.
☐ D) Make sure that your data is normalized.
☐ E) Enforce a maximum depth for the tree.
☐ F) Use “entropy” to calculate the information gain. (2 marks)
2- Which of the following statements about Neural Networks is/are true? [Select all the correct statements].
☐ A) Optimize a convex cost function.
☐ B) Always output values between 0 and 1.
☐ C) Can be used in an ensemble.
☐ D) Can be used for regression as well as classification. (2 marks)
3- In neural networks, what is/are true about the nonlinear activation functions such as sigmoid, tanh, and ReLU? [Select all the correct statements].
☐ A) Used to speed up the gradient calculation in backpropagation, as compared to linear units
☐ B) Are applied only to the output units
☐ C) Help to learn nonlinear decision boundaries
☐ D) Always output values between 0 and 1 (2 marks)