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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Students have asked these similar questions
The paper "The Effects of Adolescent Volunteer Activities on the Perception of Local Society and Community Spirit Mediated by Self-Conception"† describes a survey of a large representative sample of middle school children in South
Korea. One question in the survey asked how much time per year the children spent in volunteer activities. The sample mean was 14.76 hours and the sample standard deviation was 16.54 hours.
USE SALT
Based on the reported sample mean and sample standard deviation, explain why it is not reasonable to think that the distribution of volunteer times for the population of South Korean middle school students is approximately
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If the distribution of volunteer times is approximately normal, for the sample standard deviation of s = 16.54 hours and the sample mean of x = 14.76 hours, approximately 19
negative. Therefore, it is not
reasonable to think that the distribution of volunteer times is approximately normal.
% of…
Suppose X|Y=1 is a Uniform(0,4) density, X|Y=0 is a Uniform(2,6) density, and
P(Y=1) = 2/3. Calculate the Bayes error, i.e., the error rate of the Bayes classifier
(you may leave your answer as a fraction).
Assume there are three hypotheses, h1, h2, h3, which are trained from the same data set D. The accuracy of the three hypotheses are P(h1) = 0.45, P(h2) =
0.3, P(h3) 0.25.
Given a new instance x, the predicted results of the three hypotheses are h1(x) = yes, h2(x) = no, h3(x) = no. (Assume binary target values of "yes" and "no.")
What is the predicted result of the Bayes optimal classifier using h1, h2, and h3?
O Yes
O No
Chapter 2 Solutions
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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