Choosing the right anomaly detection algorithm seems quite hard at the moment. It might be because I am bombarded with so many alternatives likes clustering, K-Means DBSCAN and so many others.
On my side I have a csv files with thousands of lines, the columns have header that either show the name of the file and the features.
Values columns is the one I want to check about anomalies, in this case I would get a lot of anomalies because the numbers belong to different units-
So first I would need to filter Unit to lets say meters and then check values column data for any anomalies
I would appreciate some advice on what would be the best approach to tackle this problem