I have a payment transaction dataset with a large number of predictor variables. I am trying to build a model for anomaly detection and I have evaluated various algorithms/approaches for the same like Isolation Forest, kNN, Autoencoders, and One-class SVM.
I am able to identify if a payment record is an anomaly or not but I am not able to pin-point the predictor variable that is causing the anomaly.
e.g.:
Account || Currency || Beneficiary || Amount || isAnomaly(target)
I want to identify if, for an anomalous record, Currency variable is causing the anomaly or Amount variable is causing the anomaly.
I have gone through the below sources amongst many others but couldn't find anything helpful.
Anomaly detection with a multivariate Gaussian vs. PCA + univariate Gaussians
Use case for Anomaly Detection using the multivariate Gaussian distribution
Anomaly detection in multivariate time series data
Anomaly Detection in multiple parameters
I have recently started my journey in data science and would be glad if someone could help me with this issue.
