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1 sigmoid function 2 Maximum likelihood estimate Mle and loss function 3 gradient drop 4 Another form of loss function and its gradient 1.1 sigmoid function Since the two classification result is 1 or 0, which is very similar to the mathematical step function, but the step function in the position of the x=0 mutation, the mutation is difficult to deal with mathematically. Therefore, the sigmoid function is generally used to fit: G (z) =11+e−z (1) g (z) ={\frac 1{1+e^{-z}}}\tag{1} Specifica
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