Does the column order in scoring dataframes matter to H2O models using mojo format?
My ML Ops team is suggesting that perhaps the reason why I'm getting different scores than they are (even though the scoring process flow in R and the mojo model is supposedly the same) is that perhaps the difference in the order of the columns in the dataframes we are each scoring having an impact. I can't actually verify for myself that they are using the exact same mojo model, etc., so I'm wondering if it's actually possible that that H2O mojo *.zip model file is ignoring the column names and simply uses the internal order of the columns for scoring purposes? It sounds far-fetched to me but wanted a second opinion. Thanks.