Publications by Jared Chappelle
MS 5333 Assignment #2
Problem 2. Carefully explain the differences between the KNN classifier and KNN regression methods The KNN regression method is used to solve regression problems, whereas the KNN classifier method is used to solves classification problems. The KNN classification method is where you identify the neighborhood of x and then estimate the probabi...
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MS 5333 Assignment #3
Problem 13 This question should be answered using the Weekly data set, which is part of the ISLR2 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 ...
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MS 5333 Assignment #4
3. This problem relates to the QDA model, in which the observations within each class are drawn from a normal distribution with a class specific mean vector and a class specific covariance matrix. We consider the simple case where \(p = 1\); i.e. there is only one feature. Suppose that we have K classes, and that if an observation belongs t...
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MS 5333 Assignment #5
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 accuracy when...
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MS 5333 Assignment #6
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 a plot...
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MS 5333 Assignment #7
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 error, a...
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MS 5333 Assignment #8
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 = ...
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