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

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.

square pyramid

step-by-step explanation:

square prism looks like nothing like that

triangular prism has a rectangular base instead of a square base

tetrahedron has a triangular base