Symmetric kullback-leibler divergence of softmaxed distributions for anomaly scores
Date:
The use of the Kullback-Leibler (KL) divergence, for probability distributions, along with a windowing scheme, is explored in this paper, for the design of anomaly scores. Distributions are built from the frequencies of a metric in a given time window. For context, KL is used to compare the distribution of the current window with that of a linear combination of several preceding windows. Ensemble-like scores may be built by using the method on independent metrics. Experiments are conducted to test the proposed method on a University of Victoria dataset and a synthetic dataset.