**Least squares** is a form of approximation, and is used to make a prediction based on experimental data.

## Example

Given a set of points , and the deviation from the points minimize by changing values *a* and *b*.

Finding the minimum involves talking a look a the derivates.

Removing unnecessary 2 constants (solving to approach 0), and simplifying:

This can be re-written as a 2x2 linear system:

Note that some systems may be more complex, and may involve more than two paramaters.

## Recursive least-squares algorithm

The Recursive least-squares formula is designed for real-time estimation, rather than performing a batch result each time an entry is added.^{[1]}

## References

- ↑ Identification, Estimation, and Learning - Lecture 2 - MIT OpenCourseware