I work with a unbalanced data set (it is about people who actually bought stuff):
Bought stuff: Yes ~ 3% Bought stuff: NO ~97%
The most important task for my machine learning model, is to optimize the sensitivity (I want to "catch" all the "Yes" people, the 3%).
But I was wondering how I could define the baseline. I read this article (https://machinelearningmastery.com/how-to-get-baseline-results-and-why-they-matter/) where is written: "Classification: select the class that has the most observarions and use that class as the result for all predictions".
But, because sensitivity is the most important, can I say that my baseline is 3% (the Yes class, because when you randomly guess.. you will guess statistically 3 people as buyers from the 100).