An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
13th Edition
ISBN: 9781461471370
Author: Gareth James
Publisher: SPRINGER NATURE CUSTOMER SERVICE
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Chapter 2, Problem 7E
a.
Explanation of Solution
Euclidean distance
| X1 | X2 | X3 | Y | Distance from origin |
| 0 | 3 | 0 | Red | 3 |
| 2 | ... |
b.
Explanation of Solution
Prediction of value k
- Prediction with K=1 is Green...
c.
Explanation of Solution
Prediction of value k
- Prediction with K=1 is Green.
- This is because t...
d.
Explanation of Solution
Bayes decision boundary
- When K becomes larger, we get a smoother boundary...
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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- Considering the threshold as 0.5, Calculate the F1 measure for attached predictions of a classification model. Group of choice: A. 1 B. 0.45 C. 0.67 D.0.53arrow_forward2. Take a bivariate normal distribution with two random variables X and Y, with mean value = (1, -1), var(X) = 3, var(Y) = 6, and cor(X,Y) = -0.5. %3! (a) create a contour plot for this data (b) plot 1,000 simulations of this distribution (c) Using 1,000,000 simulations, find (1) the expected value of Y (ii) the expected value of Y, given that X> 2 (ii) the expected value of Y, given that X = 2arrow_forward2. Can you design a binary classification experiment with 100 total population (TP+TN+FP+ FN), with precision (TP/(TP+FP)) of 1/2, with sensitivity (TP/(TP+FN)) of 2/3, and specificity (TN/(FP+TN)) of 3/5? (Please consider the population to consist of 100 individuals.)arrow_forward
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- Exercise 10 Of the sampling distributions from 2 and 3, which has a smaller spread? If you're concerned with making estimates that are more often close to the true value, would you prefer a sampling distribution with a large or small spread?arrow_forwardWhat is answer ? Q1: Suppose you are working on weather prediction, and use a learning algorithm to predict tomorrow's temperature (in degrees Centigrade/Fahrenheit). Would you treat this as a classification or a regression problem? Q2: Suppose you are working on stock market prediction. You would like to predict whether or not a certain company will declare bankruptcy within the next 7 days (by training on data of similar companies that had previously been at risk of bankruptcy). Would you treat this as a classification or a regression problem?arrow_forwardA dataset consists of 1,000 elements. Using cross-validation, the sample error rate of hypothesis h1 is found to be 0.07 and that of hypothesis h2 is 0.11. Give the confidence intervals of the two errors and comment how that relates to the statistical difference between the results. ZN =1.96 for a confidence level of 95%.arrow_forward
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