Linear Regression is the bicycle of regression models. It’s simple yet incredibly useful. It can be used in a variety of domains. It has a nice closed formed solution, which makes model training a super-fast non-iterative process.

A Linear Regression model’s performance characteristics are well understood and backed by decades of rigorous research. The model’s predictions are easy to understand, easy to explain and easy to defend.

If your data satisfies the assumptions that the Linear Regression model, specifically the Ordinary Least Squares Regression (OLSR) model makes, in most cases you need look no further.

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Assumptions of Linear Regression
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