Paranom: A Parallel Anomaly Dataset Generator

Gottschlich, Justin

arXiv.org Machine Learning 

In this paper, we present Paranom, a parallel anomaly dataset generator. We discuss its design and provide brief experimental results demonstrating its usefulness in improving the classification correctness of LSTM-AD, a state-of-the-art anomaly detection model.

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