I have a binary classification problem where I'm required to classify transactions as anomalous or normal (1 or 0 respectively), with anomalies being the rarer instance.
With what I know to be true from experience about the domain & the ecosystem where the transactions happen, I chose 4 variables out of many and ran a logistic regression. Sure enough, all 4 variables were 'very significant'.
My question is, did I just indulge in data dredging (or any other less-than-ideal practice) by cherry-picking my variables before-hand without checking if they are statistically significant independently, or is this a benign case of domain knowledge in action?
EDIT: I wanted to tag
data-dredging, but couldn't.