# What is Regression?

The goal of regression is to determine which factors are most important, which can be ignored, and how the features interact with each other. In addition to solving for the target variable, this approach will provide an error rate of its predictions, illustrating just how well the model performs in its estimates.

Regression analysis uses mathematical functions to estimate a continuous dependent variable from a list of input features. There are several regression techniques – linear regression is the simplest, while other models like neural networks are more complex.

Simple regression analysis works with one variable for each dependent variable, and multiple regression uses multiple variables for each dependent variable.

Multiple regression analysis can be utilized to determine if there is a statistically significant relationship between variables as well as to find trends in datasets.

### Why is Regression Valuable?

Regression is one of the most important types of data analysis that businesses can utilize to make data-driven decisions. Regression analysis is used frequently in data science, as the use of these algorithms provides essential insights that can be used to make strategic decisions.

This type of analysis is essential for machine learning models that deal with continuous streams of numbers, such as financial analysis, weather analysis, or time-series forecasting. Many businesses use regression to answer questions like why did their sales drop, or what their projected sales will look like for the next six months.

It is important to note, however, that you cannot always attribute correlation to causation – additional analysis should be done to support decisions driven by regression.

### Regression and LogicPlum

LogicPlum’s sophisticated machine learning platforms help you use regression analysis to gain insights into trends within your business without the need for the manual work that typically goes into it. Our tools automate regression analysis so that you can work with many datasets and easily change target variables as needed.

We will also recommend whether the machine learning model you are working on is better suited for regression analysis or classification, and our experts will be there to help you use this knowledge to gain a competitive advantage in your industry.