Machine Learning Week 3: Hypothesis representation for Classification problems
Published in
1 min readFeb 10, 2017
Sigmoid Function or also called Logistic Function is one of the functions that can be used to represent out hypothesis for Classification problems(Binary Classification to be exact)
The graph of this function looks like this:
As we can see, the values for the sigmoid function does not get bigger than 1 nor it gets lesser than 0. This is what makes it good for classification because our classification problem can only have values within the range (0,1).
In mathematical terms the function is represented as:
