I\'ve created an xgboost classifier in Python:
train is a pandas dataframe with 100k rows and 50 features as columns. target is a pandas series
xgb_cla
I have tried all solutions on this page, but none worked.
As I was grouping time series, certain frequencies created gaps in data. I solved this issue by filling all NaN's.