What are some applications of Linear Regression?

Data Science, AI and ML
#1

Some applications of Linear Regression :

  • Forecasting

A top advantage of using a linear regression model in machine learning is the ability to forecast trends and make predictions that are feasible. Data Scientist can use these predictions and make further deductions based on machine learning. It is quick, efficient, and accurate. This is predominantly since machines process large volumes of data and there is minimum human intervention. Once the algorithm is established, the process of learning becomes simplified.

  • Beneficial to small businesses

By altering one or two variables, machines can understand the impact on sales. Since deploying linear regression is cost-effective, it is greatly advantageous to small businesses since short- and long-term forecasts can be made when it comes to sales. This means that small businesses can plan their resources well and create a growth trajectory for themselves. They will also be to understand the market and its preferences and learn about supply and demand.

  • Preparing Strategies

Since machine learning enables prediction, one of the biggest advantages of a linear regression model in it is the ability to prepare a strategy for a given situation, well in advance, and analyze various outcomes. Meaningful information can be derived from the regression model of forecasting thereby helping companies plan strategically and make executive decisions.