Machine Learning

Q2) [23 pts] Multiple Choice Questions a) [3 pts] In k-fold cross-validation, as we increase k, average cross-validation error will: A) increase B) decrease C) stay the same D) can't tell b) ) [3 pts] For a neural network, which of the following choices most strongly affects the tradeoff between under-fitting and over-fitting? A) The initial weights B) The learning rate C) The number of hidden nodes D) The choice of the online or batch learning algorithm c) [3 pts] Imagine you are using a k-Nearest Neighbor classifier on a dataset with lots of noise. You want your classifier to be less sensitive to the noise. Which of the following is likely to help and with what side effect? A) Increase the value of k Increase in prediction time B) Decrease the value of k Increase in prediction time C) Increase the value of k Decrease in prediction time D) Decrease the value of k Decrease in prediction time