parametersneural-networkinitializationlogistic-regression
Why do weight parameters of logistic regression get initialized to zeros?
I have seen the weights of neural networks initialized to random numbers so I am curious why the weights of logistic regression get initialized to zeros?
Solution
Incase of Neural Networks there n neurons in each layer. So if you initialize weight of each neuron with 0 then after back propogation each of them will have same weights :
Neurons a1 and a2 in the first layer will have same weights no matter how long you iterate. Since they are calculating the same function.
Which is not the case with logistic regression its simply y = Wx + b.
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