Publications by Tiffany Lecong, FVK826
HW7
Chapter 8 Question 3 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 x-axis should display ˆpm1, ranging from 0 to 1, and the y-axis should display the value of the Gini index, classification er...
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HW5
Chapter 6 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 predictio...
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DA6543 HW4
Chapter 5 Question 3 We now review k-fold cross-validation. (a) Explain how k-fold cross-validation is implemented. The set of observations are randomly divided into k groups at about equal parts. The first fold is treated as a validation set and is fit on the remaining folds. The MSE is computed on the observation of the held-out fold. This pr...
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HW 8
Chapter 9 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. Generate a data set with n = 500 and...
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STA6543_HW2
Chapter 03 Problem 2 Carefully explain the differences between the KNN classifier and KNN regression methods. KNN classifiers result in the qualitative classification output for Y. KNN regression predicts the quantitative value for f(x). Problem 9 This question involves the use of multiple linear regression on the Auto data set. (a) Produce a ...
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STA6543_HW3
Chapter 4 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. Produce some numerical and graphical summarie...
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STA6543 Assignment 6
Chapter 7 Question 6 In this exercise, you will further analyze the Wage data set considered throughout this chapter. library(ISLR) ## Warning: package 'ISLR' was built under R version 3.6.3 attach(Wage) (a) Perform polynomial regression to predict wage using age. Use cross-validation to select the optimal degree d for the polynomial. What degre...
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