Regression — 7 Regression Techniques you should know!

Regression analysis is a form of predictive modeling technique which investigates the relationship between a target and predictor. This technique is used for forecasting, time series modeling, and finding the causal effect relationship between the variables.

Why do we use Regression Analysis?

There are multiple benefits of using regression analysis. They are as follows:

1. It indicates the significant relationships between a dependent variable and the independent variable.
2. It indicates the strength of the impact of multiple independent variables on a dependent variable.

How many types of regression techniques do we have?

We will cover 7 different regression types in this article. As part of this article, we will discuss theoretically below-mentioned 7 regression types. In the following article of this Regression series, we will discuss, how we can apply regression models on different problems to predict the outcome.

· Linear Regression

· Logistic Regression

· Polynomial Regression

· Stepwise Regression

· Ridge Regression

· Lasso Regression

· Elastic Net Regression

1) Simple Linear Regression

It is one of the most widely known modeling techniques. Simple linear…