# why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ?

Thank you

• You can try using the ReLU activation function. Sep 11, 2019 at 11:48
• ShubhamPanchal I need to calculate probability that is why I assume I am tied to sigmoid Sep 11, 2019 at 12:51
• if the function value becoming 0 or 1 due to float precision issues you could just add/subtract a small epsilon (like 1e-6), this should not hurt your results Sep 11, 2019 at 14:21

When you have very large weights because of the activation sigmod(w^tx + b) where w and b your large weights you will end up with passing a very large positive or negative number to sigmoid functions. Very large positive number will return 1 and similarly very large negative number will return 0 by the sigmoid function (as shown in sigmoid graphs)).