I have set of 300,000 set of rows with credit card transactions and my job is to find outliers (suspicious transactions) in those dataset.
I have created around 5 features (All continuous data, with 1 column as transaction id)
I need to return list of all transaction id,which looks suspicious
What have I tried
I have tried using K means algorithm, but it does does not fit my laptop's memory (8 GB) and it crashes.
I wanted to try 1 class SVM, but I do not see any good tutorial to get me started. I tried scikitlearn official tutorial, but it already has outliers added to it and they are just plotting it.
How do I automatically detect the outliers and return those observations ?