
#1




Ch 1: Question on f and h functions
Okay I understand that the h function is what we're after. There can be many h functions from the hypothesis space H and we're after the h function that models the data optimally. The f function has been repeatedly stated as unknown. What I don't understand is page 21, the equation. How can the "fraction D where f and h disagree" be an accurate statement when f is considered unknown. Can't test if they disagree when f is unknown to begin with. I hope someone can clarify this for me.

#2




Re: Ch 1: Question on f and h functions
Okay I got it. The f function is what's being learned which gets continually compared to the hypothesis. Going back to Mitchel's book on Machine Learning. The f function would be the target concept function.

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