Characteristics of regression and classification algorithms

In this section, we’ll explore the characteristics of a range of different regression and classification algorithms. We will explore their practical applications and how they can be used to drive decision-making in various industries.

Regression algorithms

We have already covered regression, which is a form of supervised machine learning. Regression algorithms are used when the output or target variable is continuous or numerical. They are primarily used for forecasting, predicting trends, and determining relationships between variables. Beyond the ordinary least squares regression we have already covered, there are other, more advanced variations of regression. These variations can be used to account for different interactions between variables, or to mitigate overfitting by applying what is known as regularization.

Polynomial regression

Polynomial regression extends linear regression by adding extra predictors...