I'm utilizing Principal Component Analysis (PCA) on a RandomForestRegressor model to process some of the text fields in my data, which results in a certain number of PCA fields (around 30, I would say). The model look good upon the initial `fit` from within the experiment window, so I saved the model and scheduled a training run to occur every morning.
However, the scheduled training fails with a 'Usecols do not match columns, columns expected but not found' failure. It normally reports a handful of PC_* fields on the higher end of the range (like PC_27 - PC_31) not being found. The error appears to be related directly to the pandas python library but I don't have the capability to troubleshoot the code itself and hoping to resolve the issue via MLTK. Can anyone assist?