Regression

What is Regression?

In the field of artificial intelligence, regression is a fundamental technique used to predict continuous outcomes. This could involve anything from estimating the future sales of a product to predicting real estate prices based on various features such as location, size, and amenities. By analyzing the patterns in historical data, regression models can identify trends and make informed predictions. It's widely used in various industries, including finance, healthcare, and marketing, to drive data-driven decision-making. The simplicity and interpretability of regression models make them a popular choice for initial data analysis. However, it's crucial to ensure the quality of the data and the appropriateness of the model to avoid misleading results.

A type of predictive modeling technique that estimates the relationship between a dependent (target) and independent variable(s) (predictors).

Examples

• Predicting House Prices: By using features like the number of bedrooms, location, and square footage, a regression model can estimate the market value of a home.


• Sales Forecasting: Retailers use regression to predict future sales based on historical sales data, seasonal trends, and promotional activities.

Additional Information

• Regression models can be linear or non-linear, depending on the relationship between variables.


• They are highly sensitive to outliers and multicollinearity, which can skew results.