Regression is a supervised machine learning technique used to predict continuous numerical values based on input data. It analyzes the relationship between independent variables (features) and a dependent variable (output) to make predictions.
In data science and machine learning, regression is commonly used for forecasting trends, estimating values, and understanding how variables influence each other. It is widely applied in business, finance, and analytics.
For example:
- A model predicts house prices based on size, location, and number of rooms.
- A sales system forecasts future revenue based on past performance data.
- A weather model estimates temperature based on historical patterns.
- A marketing team predicts customer spending behavior.
Common types and concepts related to regression include:
- Linear Regression
- Multiple Regression
- Polynomial Regression
- Supervised Learning
- Training Data
- Dependent & Independent Variables
- Error / Loss Function
- Model Prediction
- Statistical Analysis
