A machine learning company claims that its classifier correctly differentiates between images of cats and dogs 7 times out of 10. You want to check this claim, and run the company's classifier on your personal set of data that contains 1; 234 images of cats and dogs. Let X, be 1 if the classifier successfully labeled image i and 0 otherwise. Let S = 1234 * X, be the number of times the classifier was right on your data set. You find empirically that S = 785 with an estimated standard deviation s = 0.48. We further suppose that the classifier guesses are independent. (a) What is the distribution of S? (b) What is the estimated success probability p? (c) What is the 95% confidence interval of the value of p based on the data set X1, X2, X1234? .....

A machine learning company claims that its classifier correctly differentiates between images of cats and dogs 7 times out of 10. You want to check this claim, and run the company's classifier on your personal set of data that contains 1; 234 images of cats and dogs. Let X, be 1 if the classifier successfully labeled image i and 0 otherwise. Let S = 1234 * X, be the number of times the classifier was right on your data set. You find empirically that S = 785 with an estimated standard deviation s = 0.48. We further suppose that the classifier guesses are independent. (a) What is the distribution of S? (b) What is the estimated success probability p? (c) What is the 95% confidence interval of the value of p based on the data set X1, X2, X1234? .....

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MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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df
甲2
1 / 1
125%
EXERCISE II
A machine learning company claims that its classifier correctly differentiates between
images of cats and dogs 7 times out of 10. You want to check this claim, and run the
company's classifier on your personal set of data that contains 1; 234 images of cats
and dogs. Let X, be 1 if the classifier successfully labeled image i and 0 otherwise.
Let S =
1234
X, be the number of times the classifier was right on your data set.
You find empirically that S = 785 with an estimated standard deviation s = 0.48. We
further suppose that the classifier guesses are independent.
(a) What is the distribution of S?
(b) What is the estimated success probability p?
(c) What is the 95% confidence interval of the value of p based on the data set X1,
X2,
(d) Is there statistically significant evidence that 0.7 is not a correct estimate for the
true probability of success of the classifier? Do you think it indicates that the
machine learning company oversold its product?
X1234?
1

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