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sesenic [268]
3 years ago
5

A supervised learning model has been built to predict whether someone is infected with a new strain of a virus. The probability

of any one person having the virus is 1%. Using accuracy as a metric, what would be a good choice for a baseline accuracy score that the new model would want to outperform
Mathematics
1 answer:
larisa [96]3 years ago
7 0

Answer:

A baseline score of 99% needs to be set.

Step-by-step explanation:

Since this is an example of a classification problem (the classes being whether somebody has been infected with a new virus or not), the ideal score to achieve in such a case is 100%. Hence, a baseline score of 99% should be set in order to get to 100% by outperforming it.

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Answer:

He needs 7 more consecutive successful first serves to raise his first serve percentage to 60%.

Step-by-step explanation:

After n consecutive serves, his total number of serves is going to be n+8, since he has already served 8 times. In the best case, his number of successful first serves is n+2.

His percentage of succesful first serves is the division of the number of succesful first serves divided by the total number of serves. So

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