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Variational autoencoder for anomaly detection in time-series data
Python 0.43%
Jupyter Notebook 99.57%
vae_time_series_anomaly_detection's Introduction
Variational autoencoder for anomaly detection in time-series data
- The dataset I used here is the Real time traffic data from the Twin Cities Metro area in Minnesota, which can be found here
- The file names are quite self-explanatory for running the model
- Model results when using a probability threshold 0.2:
- TODO: replace MLP encoder decoder to LSTM encoder decoder
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