Lets talk about some applied mathematics... there's alot of field that we could carry out.
One of fields is classifying datasets.
Lets supose, we have two datasets that come from a measures of some medical treatment, A and B, and we want to know if A and B are not correlated, it means , the variations on the medical treatment A are independent to the variation of B.
On my research, we can solve this problem creating two straight lines (2D) or hyperplanes (3D or more) maximizing the gap between them. The method using to solve this problem is linear programming because of the simplicity and consistent.
The results of the method will give us the information of the straight lines (hyperplanes) and the gap between them. If the gap exist and it's positive then the two datasets A and B are not correlated.
There are some results of my work
Classification of two datasets 2D (straight lines)
Classification of two datasets 3D (hyperplanes)
If you want more detail, the reference of my article is:
https://www.researchgate.net/publication/304781898_Criterio_de_Clasificacion_de_Datos_usando_Programacion_Matematica
Enjoy !!
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