Hello! I have built a regression model with a total number being the dependent variable. While building I found that the predict numbers on test dataset are not even close to the actual test values which are being presented as float values as such array([4.20544375e+03, 4.02993850e+05, 2.04953309e+06, 1.06663500e+04,
4.04249688e+04, 5.66517500e+04, 3.25695500e+04, 1.62638000e+04,
5.88910625e+03, 3.54556875e+03,..............

While debugging I found that even the describe function is presenting these values as float as well:

count 1.535000e+03
mean 4.615274e+05
std 9.623142e+05
min 0.000000e+00
25% 4.907000e+03
50% 3.677500e+04
75% 3.865015e+05
max 7.319610e+06
Name: TotalValue, dtype: float64

Can anyone guide me on what is going on and how I can fix it. Please consider that I am new to machine learning. Thank you.