Logistic regression determines the degree of dependence between the categorical dependent and one or more independent variables by using the logistic function. It aims to find the values of the coefficients for the input variables, as with linear regression. The difference, in the case of logistic regression, is that the output value is converted by using a non-linear (logistic) function. The logistic function essentially looks like a big letter S and converts any value to a number in a range from 0 to 1. This property is useful because we can apply the rule to the output of the logistic function to bind 0 and 1 to a class prediction. The following screenshot shows a logistic function graph:
For example, if the result ...
