TECH NEWS
Correlation Is Not Enough: Selecting Features Without Throwing Away Predictive Information
Dropping every feature whose correlation with the target is below 0.1 feels like hygiene. It is often the opposite: you are deleting signal your model could have used, and you will never see it in your metrics because the comparison you would need is the one you never ran.