As a beginner in machine learning, I’m trying to understand the usefulness of each model and each type of algorithm.
I saw, like a lot of people, the beginner example about the supervised learning on the titanic data set. I’m in internship in a company and i’m trying to apply a supervised model base on finance data like the invoicing, rebate, compliance…etc so i’m trying to have idea to apply a supervised learning model to my data.
But i wondering a question about the titanic data set which consist to predict if a passenger has survived or not. Well i don’t see how it is useful to build an algorithm that predict if a passenger survives or not. Let me take you and example : the case of the classification SPAM/NO SPAM for email is clearly useful because we receive new email each day but for the titanic example, we have the full data so i don’t see the point here.
Could you explain to me or maybe i wasn’t clear enough ?