Random forest error

I am conducting a random forest regression in Exploratory, and this error keeps showing up:
‘Evaluation error: data (x) has 0 rows.’
I get something similar when I try MICE in RStudio:
‘Error in cor(xobs[, keep, drop = FALSE], use = “all.obs”) : ‘x’ is empty.’
So perhaps there’s something wrong with my data rather than an operational issue?
Anyway, thanks for any help or suggestions.

Hi Conn, does “Variable Importance” analytics view work on your data?
It runs Random Forest inside, and many times it runs fine even on data with which regular Random Forest ends up with error, because we work around many known possibility of errors by automatically preprocessing the data in our wrapper function.
If it runs fine, you might be able to find the kind of preprocessing that would fix the error by checking what we do in the wrapper function. The source code is here on github. The function name is calc_feature_imp.
If you get error even with Variable Importance analytics view, let me know.

Thanks Hideaki. It does indeed work through Variable Importance.
However, as I asked about in a previous post, I would like to select all the variables as candidate predictors, but the column selector dialog only allows one to choose from among the first 300 hundred. So - as you see in that post - I was advised to carry out Random Forest through ‘+’ > Build Model > Random Forest > Regression.
Also, I see that in the Variable Importance analytics, there is no ‘Importance Table’ view, or ‘Prediction Matrix’ (as in the tutorial: https://docs.exploratory.io/analytics/var_importance.html).
I don’t know much about data science or code, so I wouldn’t be able to find the preprocessing or to fix the error. If you have any further advice, I would be very grateful. Otherwise, I’ll try to use the ‘Variable Importance’ analytics as they are shown, or to find other solutions for building strong predictive models for my outcome variables.
By the way, would you or anyone happen to know anything about the MICE package for multiple imputations? I was also given help for this through the very generous and kind Exploratory support team. However, I am getting an error in that procedure: Error in cor(xobs[, keep, drop = FALSE], use = “all.obs”) : ‘x’ is empty.
Anyway, thanks again!