There are 39 nodes that can be used as successor
for a node with an output port of type Tree Ensemble.
Extracts individual decision trees from a tree ensemble model.
Loop end node for learning an ensemble model with boosting
Collects and combines all models provided during the loop iterations.
Converts a model input into a single table cell.
2D Convolutional Long-Short Term Memory (LSTM) layer.
2D Convolutional Long-Short Term Memory (LSTM) layer.
Fast GRU implementation backed by CuDNN.
Fast GRU implementation backed by CuDNN.
Fast LSTM implementation backed by CuDNN.
Fast LSTM implementation backed by CuDNN.