Logistic Regression Code in Python for absolute beginners
Brief about Logistic Regression Algorithm When we need to predict o the class where the predicted variable has a set of defined values like yes or no, we use Logistic Regression. Difference between Logistic and Linear Regression In Linear Regression, the value predicted variable is continuous whereas, in Logistic Regression, the value predicted variable is discrete. Maths behind Logistic Regression Logistic Regression uses the Sigmoid function. Its maximum value is 1 & the minimum value is 0 and 'e' is Euler's number which is equal to 2.71828. now to perform classification in Logistic Regression, we replace z by the equation of a straight line, modifying the function to Note - to understand the equation of a straight line read Linear Regression Code in Python for absolute beginners. How Classification is done? When the value of the function comes out to be more than 0.5 then it will be class A and when...