BoostedTreesUpdateEnsembleV2

public final class BoostedTreesUpdateEnsembleV2

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

or by starting a new tree.

class BoostedTreesUpdateEnsembleV2.Options Optional attributes for BoostedTreesUpdateEnsembleV2

String OP_NAME The name of this op, as known by TensorFlow core engine

static BoostedTreesUpdateEnsembleV2

create(Scope scope, Operand<?> treeEnsembleHandle, Iterable<Operand<TInt32>> featureIds, Iterable<Operand<TInt32>> dimensionIds, Iterable<Operand<TInt32>> nodeIds, Iterable<Operand<TFloat32>> gains, Iterable<Operand<TInt32>> thresholds, Iterable<Operand<TFloat32>> leftNodeContribs, Iterable<Operand<TFloat32>> rightNodeContribs, Iterable<Operand<TString>> splitTypes, Operand<TInt32> maxDepth, Operand<TFloat32> learningRate, Operand<TInt32> pruningMode, Options... options)

Factory method to create a class wrapping a new BoostedTreesUpdateEnsembleV2 operation.

static BoostedTreesUpdateEnsembleV2.Options

logitsDimension(Long logitsDimension)

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

The name of this op, as known by TensorFlow core engine

Constant Value: "BoostedTreesUpdateEnsembleV2"

Factory method to create a class wrapping a new BoostedTreesUpdateEnsembleV2 operation.

scope	current scope
treeEnsembleHandle	Handle to the ensemble variable.
featureIds	Rank 1 tensor with ids for each feature. This is the real id of the feature that will be used in the split.
dimensionIds	List of rank 1 tensors representing the dimension in each feature.
nodeIds	List of rank 1 tensors representing the nodes for which this feature has a split.
gains	List of rank 1 tensors representing the gains for each of the feature's split.
thresholds	List of rank 1 tensors representing the thesholds for each of the feature's split.
leftNodeContribs	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.
rightNodeContribs	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.
splitTypes	List of rank 1 tensors representing the split type for each feature.
maxDepth	Max depth of the tree to build.
learningRate	shrinkage const for each new tree.
pruningMode	0-No pruning, 1-Pre-pruning, 2-Post-pruning.
options	carries optional attributes values

logitsDimension	scalar, dimension of the logits