Logistic Regression
In the Linear Regression post we discussed about the 5 main questions of the Machine Learning Universe. Similarly in this post we will try to explain one of the Classification algorithm, Logistic Regression using these 5 questions- What Training Data is used? What Mathematical Function is used? Which Loss Function is used? How is the model trained? What Metric is used for evaluation? Classification From its name, it feels like this method has something to do with classification of some sort of data. Yes!! its True. Classification is a type of Supervised machine learning Algorithm and like any other supervised learning algorithms we have a data-set with some feature variables and a target variable. The only difference between this method and Linear Regression method is, its type of target variable. In Linear Regression we study CONTINUOUS target variable where as in Classifications we study DISCRETE target variables. These discrete values of the target variables denote the different ...