Linear Programming 5: Example application - Fitting a line

Linear Programming 5: Example application - Fitting a line Abstract: We show how to setup a linear program to find a line of best fit. Whereas an L^2 line of best fit (minimizing the sum of squared errors) can be found using linear regression, an L^1 line of best fit (minimizing the sum of absolute values of errors) can be found via a linear programming. An L^1 line of best fit is less sensitive to outliers. This video accompanies the class "Linear Programming and Network Flows" at Colorado State University https://www.math.colostate.edu/~adams/teaching/math510fall2020/ We are following the book "Understanding and Using Linear Programming" by Jiří Matoušek and Bernd Gärtner https://link.springer.com/book/10.1007/978-3-540-30717-4 Our course notes are available at https://www.math.colostate.edu/~adams/teaching/math510fall2020/LinearProgrammingNotes.pdf