A method (100) of constructing a probabilistic graphical model (10) of a system from data that includes both normal and anomalous data includes the step of learning parameters of a structure for the probabilistic graphical model (10). The structure includes at least one latent variable (26) on which other variables (12, 14, 16, 18, 20, 22, 24) are conditional, and has a plurality of components. The method further includes the steps of: iteratively associating one or more of the plurality of components of the latent variable (26) with normal data; constructing a matrix of the associations; detecting abnormal components of the latent variable (26) based on one of a low association with the normal data or the matrix of associations; and deleting the abnormal components of the latent variable (26) from the probabilistic graphical model (10).