Publications by Jiwhan Yoo
Assignment 2
Question 2 Carefully explain the differences between the KNN classifier and KNN regression methods. A: KNN regression method is closely related to the KNN classifier. KNN classifier is used to solve classification problems. It first identifies the K points in the training data closest to x0, then estimates the conditional probability for class j...
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Assignment 4
3. We now review k-fold cross-validation (a) Explain how k-fold cross-validation is implemented. A: k-fold cross-validation is implemented by taking the set of n observations and randomly splitting into k non-overlapping groups. The groups act as a validation set and the remainter acts as the training set. The test error is estimated by averera...
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Algorithms 2 - Assignment 5
Question 2 For parts (a) through (c), indicate which of i. through iv. is correct. Justify your answer. (a) The lasso, relative to least squares, is: i. More flexible and hence will give improved prediction accuracy when its increase in bias is less than its decrease in variance. ii. More flexible and hence will give improved prediction accura...
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Algorithms 2 - Assignment3
Question 10 This question should be answered using the Weekly data set, which is part of the ISLR package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1,089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010. (a) Produce some numerical and graphical summaries of t...
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Algorithms 2 - Assignment 6
Question 6 In this exercise, you will further analyze the Wage data set considered throughout this chapter. (a) Perform polynomial regression to predict wage using age. Use cross-validation to select the optimal degree d for the polynomial. What degree was chosen, and how does this compare to the results of hypothesis testing using ANOVA? Make ...
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Assignment 7
Question 6 Consider the Gini index, classification error, and entropy in a simple classification setting with two classes. Create a single plot that displays each of these quantities as a function of ˆpm1. The xaxis should display ˆpm1, ranging from 0 to 1, and the y-axis should display the value of the Gini index, classification error, and ent...
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Algorithms 2 - Assignment 8
Question 5 We have seen that we can fit an SVM with a non-linear kernel in order to perform classification using a non-linear decision boundary. We will now see that we can also obtain a non-linear decision boundary by performing logistic regression using non-linear transformations of the features. (a) Generate a data set with n = 500 and p = 2...
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