In my Artificial Intelligence class the teacher addressed the subject regarding neural networks, which in this case, neural networks have the layers, such as: input , hidden and output and the neurons that compose them.
However, he cited the term bias which seems to me to be a neuron, but this term has left me more confused about neural networks and I would like to have this clarified doubt. >
What would Bias be about neural networks?
Simply put, Bias is an input of value "1" associated with a weight "b" in each neuron. Its function is to increase or decrease the net input, in order to translate the activation function on the axis.
Example:
To approximate a set of points to a line, we use y = a*x + b*1 , where a and b are constants. x is an entry associated with a weight a and we have a weight b associated with the entry 1 .
Now imagine that the network activation function is a linear function.
