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.
I’m my case this is how the file would look like, keep in mind the file is way larger.
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