# Find anomalies from records of categorical data

I have a data-set with m observations and p categorical variables (nominal), each variable X1,X2...Xp 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!

• You should as well add some tags to your question ie. dataset. – quintumnia Feb 28 '18 at 11:51
• Welcome to Stack:AI! I've taken the liberty of adding a couple of tags. :) – DukeZhou Feb 28 '18 at 18:59