Publications by Trevon Perry
STA6543-Perry-Assignment-7-Chap8
Chapter 08 (page 332): 3, 8, 9 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 p̂ m1 . The x-axis should display p̂ m1 , ranging from 0 to 1, and the y-axis should display the value of the Gini index, cla...
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STA6543-Perry-Assignment-3
Chapter 04 (page 168): 10, 11, 13 Exercises Question 10. Question 10.a. - Produce some numerical and graphical summaries of the Weekly data. Do there appear to be any patterns? attach(Weekly) summary(Weekly) ## Year Lag1 Lag2 Lag3 ## Min. :1990 Min. :-18.1950 Min. :-18.1950 Min...
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STA6543-Perry-Assignment-2
Chapter 3 Exercises Question 2 - Carefully explain the differences between the KNN classifier and KNN regression methods KNN classifier makes estimates based on the most frequent observations. KNN regression estimates f(x0) using the average of the K training observations. Question 9 - This question involves the use of multiple linear regressio...
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STA6543-Perry-Assignment-4
Chapter 05 (page 197): 3, 5, 6, 9 We now review k-fold cross validation 3.a. Explain how k-fold cross-validation is implemented This approach involves randomly k-fold CV dividing the set of observations into k groups, or folds, of approximately equal size. 3.b. What are the advantages and disadvantages of k-fold cross-validation relative to: 3.b...
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STA6543-Perry-Assignment-5
Chapter 06 (page 259): 2, 9, 11 For parts (a) through (c), indicate which of i. through iv. is correct. Justify your answer. 2.a. The lasso, relative to least squares, is: Less flexible and hence will give improved prediction accuracy when its increase in bias is less than its decrease in variance. Very similar reasoning to the ridge regressio...
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STA6543-Perry-Assignment-7
Chapter 07 (page 297): 6, 10 In this exercise, you will further analyze the Wage data set considered throughout this chapter. library(ISLR) library(boot) attach(Wage) data(Wage) 6.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 d...
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STA6543-Perry-Assignment-8
Chapter 09 (page 368): 5, 7, 8 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. 5.a. Generate a data set wi...
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