I have a dataset of 3500 samples where delay (dependent variable) depends on multiple system variables,such as cpu, memory, etc.
I can use a multiple regression model and predict the delay against a baseline (one system to be used as a baseline), or speedup, therefore instead of dealing with:
Delay values: 1000, 1500, 2000, 3000, ...
I deal with (for example,
3000 as the baseline):
Speedup ratios: 3, 2, 3/2, 1, ...
I understand that I have changed
y = ax1 + bx2 + .. +c to
1/y = ax1 + bx2 + .. + c
So, the results of my regression model on
R2 Score: 0.76 RMSE: 246.82 MAE: 173.31 Range of values is 0-3000, hence Normalised RMSE (NRMSE): 246.82/3000= 0.082
And the result of my regression model on
R2 Score: 0.96 RMSE: 70.30 MAE: 43.86 Range of ratios is 0-4000, hence Normalised RMSE (NRMSE): 70.30/4000 = 0.017
Question: The use of a baseline was quite specific to my problem (as speedup made sense). And now I am wondering if such a conversion (inversing the outcome variable) would work for any other regression examples? Is this even common? or in other words, how would I know if conversions like that would work for a regression problem (is it called reverse linear)? In general, are there any clues I should be looking for?