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I love this and I'm stealing this but I think you maybe didn't take it far enough. To extend your analogy,

Statistics is for places where making meaning of or taking action on the answer must (for practical or normative reasons) include the process

Machine learning is for places where meaning or action can be done without regard for the process.




So, you're saying ML is for situations in which type II errors are considered irrelevant?


Given that every semester is have at least one student who can't conceptualize type II errors and at least one who just can't accept type I error...I don't even k ow anymore




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