# Find anomalies from records of categorical data

I have a data-set with $$m$$ observations and $$p$$ categorical variables (nominal), each variable $$X_1, X_2,\dots, X_p$$ has several different possible values.

Ultimately, I am looking for a way to find anomalies i.e. to identify rows for which the combination of values seems incorrect with respect to the data I saw so far.

So far, I was thinking about building a model to predict the value for each column and then build some metric to evaluate how different the actual row is from the predicted row.

I would greatly appreciate any help!