Logistic regression is a commonly used model in various industries such as banking, healthcare because when compared to other classification models, the logistic regression model is easily interpreted.

Binary Classification

Binary classification is the most commonly used logistic regression. Some of the examples of binary classification problems are:

• A finance company wants to know whether a customer is default or not
• Predicting an email is spam or not
• Whether a person is diabetic or not

The binary classification always has only two possible outcomes, either ‘yes’ & ‘no’ or ‘1’ & ‘0’ etc.

Like in the previous article “Multiple Linear Regression model, “ one independent variable is often not enough to capture all the uncertainties of the logistic regression’s target variable.

#classification #machine-learning #sensitivity #logistic-regression #python