Data Glossary Lab

Logistic regression is a regression algorithm that uses a logistic function on the input features to predict the class probability or directly the class label for the target variable. In the second case, the output represents a set of categories instead of continuous values, meaning that the logistic regression acts here as a classification technique. A typical data science use case for logistic regression is predicting the likelihood of customer churn.

Linear regression is a regression algorithm that deals with modeling a linear relationship between a continuous target variable and one or several continuous features. A typical example of data science using linear regression is price prediction based on various input attributes.