EmBeD data

<b>EmBeD</b>,<i> Energy-based anomaly detector in the cloud</i>, is an approach to detect anomalies at runtime based on the free energy of a Restricted Boltzmann Machine (RBM) model. The free energy is a stochastic function that can be used to efficiently score anomalies for detecting outliers. EmBeD analyzes the system behavior from raw metric data, does not require extensive training with seeded faults, and classifies the relation of anomalous behaviors with future failures with very few false positives. The file data.zip contains the dataset used for validating <i>EmBeD</i>.