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LSTM-GAN

This repository contains an adaptation of the technique proposed by Taymouri et al. [1] for the generation and evaluation of event logs made up of sequences of activities, start and complete timestamps.

This repository containing the original source code from the authos.

[1] F. Taymouri, M. la Rosa, S. Erfani, Z. D. Bozorgi, and I. Verenich, Predictive business process monitoring via generative adversarial nets: The case of next event prediction. Springer International Publishing, 2020.

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LSTM (GAN) approach for event logs generation

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