There are 42 nodes that can be used as successor
for a node with an output port of type H2O Model.
Simple RNN layer.
Converts H2O models to MOJOs.
Apply a Principal Component Analysis model using H2O.
Apply a clustering model to an input dataset.
Apply a clustering model to an input dataset.
Apply an Isolation Forest model to an input dataset.
Predicts patterns according to the provided H2O classification model.
Predicts patterns according to the provided H2O classification model.
Predicts numerical values according to the provided H2O regression model.
The loop end node for an active learning loop.