Classification is the most utilized technique in the area of machine and statistical learning. Most machine learning problems are classification problems, such as detecting spam emails, analyzing financial risk, churn analysis, and discovering potential customers.
Classification can be of two types: binary and multi-class classification. Binary classification target variables have only two values: either 0 and 1 or yes or no. Examples of binary classification are whether a customer will buy an item or not, whether the customer will switch or churn to another brand or not, spam detection, disease prediction, and whether a loan applicant will default or not. Multi-class classification has more than two classes, for example, for categories of news articles, the classes could be sports, politics, business, and many more.
Logistic regression is one of the classification methods, although its name ends with regression. It is a commonly used binary class...