Just a hypothetical: if I made half of my instances just random numbers (both the labels and features are random although standardized in a similar way to the real data), and then the other half is legitimate real data points, would the XGBoost algorithm be able to handle it by itself? Or would I have to weight the random data lower / remove it altogether for the best results?
