tf.raw_ops.BoostedTreesUpdateEnsembleV2

Updates the tree ensemble by adding a layer to the last tree being grown

tf.raw_ops.BoostedTreesUpdateEnsembleV2(
    tree_ensemble_handle, feature_ids, dimension_ids, node_ids, gains, thresholds,
    left_node_contribs, right_node_contribs, split_types, max_depth, learning_rate,
    pruning_mode, logits_dimension=1, name=None
)

or by starting a new tree.

tree_ensemble_handle A Tensor of type resource. Handle to the ensemble variable.
feature_ids A list of at least 1 Tensor objects with type int32. Rank 1 tensor with ids for each feature. This is the real id of the feature that will be used in the split.
dimension_ids A list of Tensor objects with type int32. List of rank 1 tensors representing the dimension in each feature.
node_ids A list with the same length as dimension_ids of Tensor objects with type int32. List of rank 1 tensors representing the nodes for which this feature has a split.
gains A list with the same length as dimension_ids of Tensor objects with type float32. List of rank 1 tensors representing the gains for each of the feature's split.
thresholds A list with the same length as dimension_ids of Tensor objects with type int32. List of rank 1 tensors representing the thesholds for each of the feature's split.
left_node_contribs A list with the same length as dimension_ids of Tensor objects with type float32. List of rank 2 tensors with left leaf contribs for each of the feature's splits. Will be added to the previous node values to constitute the values of the left nodes.
right_node_contribs A list with the same length as dimension_ids of Tensor objects with type float32. List of rank 2 tensors with right leaf contribs for each of the feature's splits. Will be added to the previous node values to constitute the values of the right nodes.
split_types A list with the same length as dimension_ids of Tensor objects with type string. List of rank 1 tensors representing the split type for each feature.
max_depth A Tensor of type int32. Max depth of the tree to build.
learning_rate A Tensor of type float32. shrinkage const for each new tree.
pruning_mode A Tensor of type int32. 0-No pruning, 1-Pre-pruning, 2-Post-pruning.
logits_dimension An optional int. Defaults to 1. scalar, dimension of the logits
name A name for the operation (optional).

The created Operation.