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Isn't that basically what they said? > The main difference between machine learning and statistics is what I’d call “β-hat versus y-hat.” (I’ve also heard it d
by gwd 6y ago
Isn't that basically what they said?
> The main difference between machine learning and statistics is what I’d call “β-hat versus y-hat.” (I’ve also heard it described as inference versus prediction.) Basically, academia cares a lot about what the estimated parameters look like (β-hat), and machine learning cares more about being able to estimate a dependent variable given some inputs (y-hat).
- fxtentacle 6y agoI tried to argue about the different ways how a prediction is made in applied statistics versus applied ML. Your argument here is more between theoretical statistics and applied statistics, or similarly between theoretical and applied machine learning.