deeplearning() -> anomaly()


“Anomaly Detection: Increasing Classification Accuracy with H2O’s Autoencoder and R” offers some great ideas around using the h2o.deeplearning() algorithm to detect anomalies.

Further, a read of this may aid in boundary detection, and further coolness via h2o.feature here.

Once you’ve got your model, drop it to a H2o POJO if required, and hook it up to your stream of data.

~ by mdavey on June 10, 2016.

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