what is hinge loss?f(x)=WT*Xi+b
a.L=(y-f(x))²
b.L=y-f(x)
c.L=|y-f(x)|
d.L=max(0,1-y*f(x))
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Often in Machine Learning we come across loss functions. For someone like me coming from a non CS background, it was difficult for me to explore the mathematical concepts behind the loss functions and implementing the same in my models. So here, I will try to explain in the simplest of terms what a loss function is and how it helps in optimising our models. I will consider classification examples only as it is easier to understand, but the concepts can be applied across all techniques.
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