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(20 pt., 5 pt. each) In machine learning, "the task of identifying what an image represents is called image classification" (if you are interested, you can read more about this here: https://www.tensorflow.org/lite/examples/image classification/overview). Suppose that an image classification model is trained to recognize images of cats. This model classifies 95% of cat images correctly (that is, it classifies them as cats) and 70% of non-cat images correctly (that is, it classifies them as not cats). Assume that the probability of an image being a cat is 40%. 6.1 What is the probability that an image is a cat if the model classifies it as a cat? 6.2 What is the probability that an image is a cat if the model classifies it as not a cat? 6.3 What is the probability that an image is not a cat if the model classifies it as a cat? 6.4 What is the probability that an image is not a cat if the model classifies it as not a cat?

(20 pt., 5 pt. each) In machine learning, "the task of identifying what an image represents is called image classification" (if you are interested, you can read more about this here: https://www.tensorflow.org/lite/examples/image classification/overview). Suppose that an image classification model is trained to recognize images of cats. This model classifies 95% of cat images correctly (that is, it classifies them as cats) and 70% of non-cat images correctly (that is, it classifies them as not cats). Assume that the probability of an image being a cat is 40%. 6.1 What is the probability that an image is a cat if the model classifies it as a cat? 6.2 What is the probability that an image is a cat if the model classifies it as not a cat? 6.3 What is the probability that an image is not a cat if the model classifies it as a cat? 6.4 What is the probability that an image is not a cat if the model classifies it as not a cat?

C++ for Engineers and Scientists
C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter13: Structures
Section: Chapter Questions
Problem 4PP
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(20 pt., 5 pt. each) In machine learning, "the task of identifying what an image represents is called image classification" (if you are interested, you can read more about this here: https://www.tensorflow.org/lite/examples/image classification/overview). Suppose that an image classification model is trained to recognize images of cats. This model classifies 95% of cat images correctly (that is, it classifies them as cats) and 70% of non-cat images correctly (that is, it classifies them as not cats). Assume that the probability of an image being a cat is 40%. 6.1 What is the probability that an image is a cat if the model classifies it as a cat? 6.2 What is the probability that an image is a cat if the model classifies it as not a cat? 6.3 What is the probability that an image is not a cat if the model classifies it as a cat? 6.4 What is the probability that an image is not a cat if the model classifies it as not a cat?
Transcribed Image Text:(20 pt., 5 pt. each) In machine learning, "the task of identifying what an image represents is called image classification" (if you are interested, you can read more about this here: https://www.tensorflow.org/lite/examples/image classification/overview). Suppose that an image classification model is trained to recognize images of cats. This model classifies 95% of cat images correctly (that is, it classifies them as cats) and 70% of non-cat images correctly (that is, it classifies them as not cats). Assume that the probability of an image being a cat is 40%. 6.1 What is the probability that an image is a cat if the model classifies it as a cat? 6.2 What is the probability that an image is a cat if the model classifies it as not a cat? 6.3 What is the probability that an image is not a cat if the model classifies it as a cat? 6.4 What is the probability that an image is not a cat if the model classifies it as not a cat?
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