A Dataset for Evaluating Online Anomaly Detection Approaches for Discrete Multivariate Time Series (Q6690641)

This record comprises the 0_simulation and 1_postsim folders. The 0_simulation folder consists of the raw.mat files, each representing a multivariate time series, whereas the 1_postsim folder consists of the following pickle files: normal.pkl, which contains all nominal sequences anomalous.pkl, which contains all anomalous sequences control.pkl, which contains all control-counterparts to anomalous.pkl training.pkl, which contains all pre-determined folds for training training_clean.pkl, a version of training.pkl without anomalous sequences testing.pkl, which contains all pre-determined folds for testing testing_clean.pkl, a version of testing.pkl without anomalous sequences Each pickle file is a list of 2D NumPy arrays, each representing a multivariate time series. The name of the corresponding .mat file (and, by extension, the label) is present in the metadata. For NumPy objectarray, it can be read by callingarray.dtype.metadata['file_name']. We decided to omit the2_preprocessed folder as the contents are specific to the TensorFlow data pipeline and the same data host limitations would apply. For more information, refer to the publication preprint on arXiv. For access to the source code, refer to the repository on GitHub