Common machine learning models
Here, we will explain some of the most common machine learning models, as well as their advantages and disadvantages. Knowing this information will help you pick the best model for the problem and be able to improve the implemented model.
Linear regression
Linear regression is a type of supervised learning algorithm that’s used to model the relationship between a dependent variable and one or more independent variables. It assumes a linear relationship between the input features and the output. The goal of linear regression is to find the best-fit line that predicts the value of the dependent variable based on the independent variables.
The equation for a simple linear regression with one independent variable (also called a simple linear equation) is as follows:
Here, we have the following:
- y is the dependent variable (the variable we want to predict)
- x is the independent variable (the input variable)
- m is the slope...