I have a dataset with $m$ observations and $p$ categorical variables (nominal), each variable $X_1,X_2...X_p$ has several different classes (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!