[21/10, 09:50] Zed: my main point is towards dealing the multi-dimensional datasets with regression models .. [21/10, 09:50] Zed: if you got the concept of multi-dimensional dataset, for example, if you take *data set-1* as,

1,2,3,4,5,6,7,8,9.....n => n used { n R n<0} or { n R : n<0} the set of all n R n>0 (n is greater than zero 0)

if you take *data set-2* as,

1,3,5,7,11,13.....n => n as a prime number and used { n N n<0} or { n N : n<0} the set of all n N n>0 (n is greater than zero 0)

please give attention that the *dataset 1* is a set of Real Numbers, whereas *dataset 2* is a set of Natural Numbers, but *Prime in nature*

we have to show the point of the regression *algorithm's (resulting/processing/etc.,) behavior* when the dimension from *dataset 1* is changed to *dataset 2* .. that's the object of the research ..

BTW, can I take it granted, that you understand these notation and usage of *dataset* representation?