Detection of Abnormal Input-Output Associations

Charmgil Hong, Siqi Liu, Milos Hauskrecht

We study a novel outlier detection problem that aims to identify abnormal input-output associations in data, whose instances consist of multi-dimensional input (context) and output (responses) pairs. We present our approach that works by analyzing data in the conditional (input--output) relation space, captured by a decomposable probabilistic model. Experimental results demonstrate the ability of our approach in identifying multivariate conditional outliers.

Knowledge Graph



Sign up or login to leave a comment