Hello!
Could anyone explain how do we get these equations, please?
Obviously, we derive them from known equations, but I’m a little confused in the calculations.
Thanks.
Welcome to the community!
This formula is that of logarithmic loss (aka log loss) or cross-entropy loss, which is a common evaluation metric for binary classification models such as logistic regression.
It tells you how close prediction probability is to the label (for instance to 0 or 1 in case of a binary classification into negative or positive classes). Having a lower loss of course implies better model performance.
Please look at any link on the topic of cross-entropy loss function.
One example I could find is section 5.5 of this pdf on Logistic Regression.
Hope this helps.
Best Regards.
– Jaidev
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Hello @getjaidev !
That’s exactly what I need 
Thank you so much!
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