Automated multiple regression model-building techniques often hide important aspects of data from the data analyst. Such features as nonlinearity, collinearity, outliers, and points with high leverage ...

Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

Nothing is set in stone with a regression model, but if the data you feed it is very good, the prediction will be good, too. What sort of data is required for machine learning regression?