Index
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form
A
- AbstractCARTTrainer<T> - Class in org.tribuo.common.tree
-
Base class for
Trainer's that use an approximation of the CART algorithm to build a decision tree. - AbstractCARTTrainer(int, float, float, float, boolean, long) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer
-
After calls to this superconstructor subclasses must call postConfig().
- AbstractCARTTrainer.AbstractCARTTrainerProvenance - Class in org.tribuo.common.tree
-
Deprecated.
- AbstractCARTTrainerProvenance(Map<String, Provenance>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
-
Deprecated.Deserialization constructor.
- AbstractCARTTrainerProvenance(AbstractCARTTrainer<T>) - Constructor for class org.tribuo.common.tree.AbstractCARTTrainer.AbstractCARTTrainerProvenance
-
Deprecated.Constructs a provenance for the host AbstractCARTTrainer.
- AbstractTrainingNode<T> - Class in org.tribuo.common.tree
-
Base class for decision tree nodes used at training time.
- AbstractTrainingNode(int, int, AbstractTrainingNode.LeafDeterminer) - Constructor for class org.tribuo.common.tree.AbstractTrainingNode
-
Builds an abstract training node.
- AbstractTrainingNode.LeafDeterminer - Class in org.tribuo.common.tree
-
Contains parameters needed to determine whether a node is a leaf.
- array - Variable in class org.tribuo.common.tree.impl.IntArrayContainer
-
The array of ints.
B
- buildTree(int[], SplittableRandom, boolean) - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
Builds next level of a tree.
C
- computeDepth(int, Node<T>) - Static method in class org.tribuo.common.tree.TreeModel
-
Computes the depth of the tree.
- convertTree() - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
Converts a tree from a training representation to the final inference time representation.
- copy() - Method in class org.tribuo.common.tree.AbstractTrainingNode
- copy() - Method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Returns a copy of the elements in use.
- copy() - Method in class org.tribuo.common.tree.LeafNode
- copy() - Method in interface org.tribuo.common.tree.Node
-
Copies the node and it's children.
- copy() - Method in class org.tribuo.common.tree.SplitNode
- copy(String, ModelProvenance) - Method in class org.tribuo.common.tree.TreeModel
- countNodes(Node<T>) - Method in class org.tribuo.common.tree.TreeModel
-
Counts the number of nodes in the tree rooted at the supplied node, including that node.
- createSplitNode() - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
Transforms an
AbstractTrainingNodeinto aSplitNode - CURRENT_VERSION - Static variable in class org.tribuo.common.tree.LeafNode
-
Protobuf serialization version.
- CURRENT_VERSION - Static variable in class org.tribuo.common.tree.SplitNode
-
Protobuf serialization version.
- CURRENT_VERSION - Static variable in class org.tribuo.common.tree.TreeModel
-
Protobuf serialization version.
D
- DecisionTreeTrainer<T> - Interface in org.tribuo.common.tree
-
A tag interface for a
Trainerso the random forests trainer can check if it's actually a tree. - DEFAULT_SIZE - Static variable in class org.tribuo.common.tree.AbstractTrainingNode
-
Default buffer size used in the split operation.
- depth - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- deserializeFromProto(int, String, Any) - Static method in class org.tribuo.common.tree.TreeModel
-
Deserialization factory.
- deserializeFromProtos(List<TreeNodeProto>, Class<U>) - Static method in class org.tribuo.common.tree.TreeModel
-
We will start off with a list of node builders that we will replace item-by-item with the nodes that they built.
E
- ensembleName() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
- ensembleName() - Method in class org.tribuo.common.tree.RandomForestTrainer
- equals(Object) - Method in class org.tribuo.common.tree.LeafNode
- equals(Object) - Method in class org.tribuo.common.tree.SplitNode
- ExtraTreesTrainer<T> - Class in org.tribuo.common.tree
-
A trainer which produces an Extremely Randomized Tree Ensemble.
- ExtraTreesTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.common.tree.ExtraTreesTrainer
-
Constructs an ExtraTreesTrainer with the default seed
Trainer.DEFAULT_SEED. - ExtraTreesTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.common.tree.ExtraTreesTrainer
-
Constructs an ExtraTreesTrainer with the supplied seed, trainer, combining function and number of members.
F
- fill(int[]) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Overwrites values from the supplied array into this array.
- fill(IntArrayContainer) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Overwrites values in this array with the supplied array.
- fractionFeaturesInSplit - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Number of features to sample per split.
G
- getDepth() - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
The depth of this node in the tree.
- getDepth() - Method in class org.tribuo.common.tree.TreeModel
-
Probes the tree to find the depth.
- getDistribution() - Method in class org.tribuo.common.tree.LeafNode
-
Gets the distribution over scores in this node.
- getExcuse(Example<T>) - Method in class org.tribuo.common.tree.TreeModel
- getFeatureID() - Method in class org.tribuo.common.tree.SplitNode
-
Gets the feature ID that this node uses for splitting.
- getFeatures() - Method in class org.tribuo.common.tree.TreeModel
-
Returns the set of features which are split on in this tree.
- getFractionFeaturesInSplit() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- getFractionFeaturesInSplit() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
-
Returns the feature subsampling rate.
- getGreaterThan() - Method in class org.tribuo.common.tree.SplitNode
-
The node used if the value is greater than the splitValue.
- getImpurity() - Method in class org.tribuo.common.tree.LeafNode
- getImpurity() - Method in interface org.tribuo.common.tree.Node
-
The impurity score of this node.
- getImpurity() - Method in class org.tribuo.common.tree.SplitNode
- getInvocationCount() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- getLessThanOrEqual() - Method in class org.tribuo.common.tree.SplitNode
-
The node used if the value is less than or equal to the splitValue.
- getMaxDepth() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
-
Gets the maximum tree depth.
- getMinChildWeight() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
-
Gets the minimum example weight of a child node.
- getMinImpurityDecrease() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- getMinImpurityDecrease() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
-
Returns the minimum decrease in impurity necessary to split a node.
- getNextNode(SparseVector) - Method in class org.tribuo.common.tree.AbstractTrainingNode
- getNextNode(SparseVector) - Method in class org.tribuo.common.tree.LeafNode
- getNextNode(SparseVector) - Method in interface org.tribuo.common.tree.Node
-
Returns the next node in the tree based on the supplied example, or null if it's a leaf.
- getNextNode(SparseVector) - Method in class org.tribuo.common.tree.SplitNode
-
Return the appropriate child node.
- getNumExamples() - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
The number of training examples in this node.
- getOutput() - Method in class org.tribuo.common.tree.LeafNode
-
Gets the output in this node.
- getPrediction(int, Example<T>) - Method in class org.tribuo.common.tree.LeafNode
-
Constructs a new prediction object based on this node's scores.
- getRoot() - Method in class org.tribuo.common.tree.TreeModel
-
Returns the root node of this tree.
- getScaledMinImpurityDecrease() - Method in class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
-
Gets the minimum impurity decrease necessary to split a node.
- getTopFeatures(int) - Method in class org.tribuo.common.tree.TreeModel
- getUseRandomSplitPoints() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- getUseRandomSplitPoints() - Method in interface org.tribuo.common.tree.DecisionTreeTrainer
-
Returns whether to choose split points for features at random.
- getWeightSum() - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
The sum of the weights associated with this node's examples.
- greaterThan - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- grow(int) - Method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Grows the backing array, copying the elements.
H
- hashCode() - Method in class org.tribuo.common.tree.LeafNode
- hashCode() - Method in class org.tribuo.common.tree.SplitNode
I
- impurityScore - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- IntArrayContainer - Class in org.tribuo.common.tree.impl
-
An array container which maintains the array and the size.
- IntArrayContainer(int) - Constructor for class org.tribuo.common.tree.impl.IntArrayContainer
-
Constructs a new int array container with the specified initial backing array size.
- isLeaf() - Method in class org.tribuo.common.tree.AbstractTrainingNode
- isLeaf() - Method in class org.tribuo.common.tree.LeafNode
- isLeaf() - Method in interface org.tribuo.common.tree.Node
-
Is it a leaf node?
- isLeaf() - Method in class org.tribuo.common.tree.SplitNode
L
- leafDeterminer - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- LeafDeterminer(int, float, float) - Constructor for class org.tribuo.common.tree.AbstractTrainingNode.LeafDeterminer
-
Constructs a leaf determiner using the supplied parameters.
- LeafNode<T> - Class in org.tribuo.common.tree
-
An immutable leaf
Nodethat can create a prediction. - LeafNode(double, T, Map<String, T>, boolean) - Constructor for class org.tribuo.common.tree.LeafNode
-
Constructs a leaf node.
- lessThanOrEqual - Variable in class org.tribuo.common.tree.AbstractTrainingNode
M
- maxDepth - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Maximum tree depth.
- merge(List<int[]>, IntArrayContainer, IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Merges the list of int arrays into a single int array, using the two supplied buffers.
- merge(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Merges input and otherArray writing to output.
- MIN_EXAMPLES - Static variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Default minimum weight of examples allowed in a leaf node.
- minChildWeight - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Minimum weight of examples allowed in a leaf.
- minImpurityDecrease - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Minimum impurity decrease.
- mkTrainingNode(Dataset<T>, AbstractTrainingNode.LeafDeterminer) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
-
Makes the initial training node.
N
- Node<T> - Interface in org.tribuo.common.tree
-
A node in a decision tree.
- numExamples - Variable in class org.tribuo.common.tree.AbstractTrainingNode
O
- org.tribuo.common.tree - package org.tribuo.common.tree
-
Provides common functionality for building decision trees, irrespective of the predicted
Output. - org.tribuo.common.tree.impl - package org.tribuo.common.tree.impl
-
Provides internal implementation classes for building decision trees.
P
- postConfig() - Method in class org.tribuo.common.tree.AbstractCARTTrainer
-
Used by the OLCUT configuration system, and should not be called by external code.
- postConfig() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
- postConfig() - Method in class org.tribuo.common.tree.RandomForestTrainer
-
Used by the OLCUT configuration system, and should not be called by external code.
- predict(Example<T>) - Method in class org.tribuo.common.tree.TreeModel
R
- RandomForestTrainer<T> - Class in org.tribuo.common.tree
-
A trainer which produces a random forest.
- RandomForestTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int) - Constructor for class org.tribuo.common.tree.RandomForestTrainer
-
Constructs a RandomForestTrainer with the default seed
Trainer.DEFAULT_SEED. - RandomForestTrainer(DecisionTreeTrainer<T>, EnsembleCombiner<T>, int, long) - Constructor for class org.tribuo.common.tree.RandomForestTrainer
-
Constructs a RandomForestTrainer with the supplied seed, trainer, combining function and number of members.
- removeOther(IntArrayContainer, int[], IntArrayContainer) - Static method in class org.tribuo.common.tree.impl.IntArrayContainer
-
Copies from input to output excluding the values in otherArray.
- rng - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
S
- seed - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
- serialize() - Method in class org.tribuo.common.tree.TreeModel
- serializeToNodes(Node<T>) - Method in class org.tribuo.common.tree.TreeModel
-
Serializes the supplied node tree into a list of protobufs.
- setInvocationCount(int) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- shouldMakeLeaf(double, float) - Method in class org.tribuo.common.tree.AbstractTrainingNode
-
Determines whether the node to be created should be a
LeafNode. - size - Variable in class org.tribuo.common.tree.impl.IntArrayContainer
-
The number of elements in the array.
- split - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- splitID - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- SplitNode<T> - Class in org.tribuo.common.tree
-
An immutable
Nodewith a split and two child nodes. - SplitNode(double, int, double, Node<T>, Node<T>) - Constructor for class org.tribuo.common.tree.SplitNode
-
Constructs a split node with the specified split value, feature id, impurity and child nodes.
- splitValue - Variable in class org.tribuo.common.tree.AbstractTrainingNode
- splitValue() - Method in class org.tribuo.common.tree.SplitNode
-
The threshold value.
T
- toString() - Method in class org.tribuo.common.tree.ExtraTreesTrainer
- toString() - Method in class org.tribuo.common.tree.LeafNode
- toString() - Method in class org.tribuo.common.tree.RandomForestTrainer
- toString() - Method in class org.tribuo.common.tree.SplitNode
- toString() - Method in class org.tribuo.common.tree.TreeModel
- train(Dataset<T>) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- train(Dataset<T>, Map<String, Provenance>) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- train(Dataset<T>, Map<String, Provenance>, int) - Method in class org.tribuo.common.tree.AbstractCARTTrainer
- trainInvocationCounter - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
- TreeModel<T> - Class in org.tribuo.common.tree
- TreeModel(String, ModelProvenance, ImmutableFeatureMap, ImmutableOutputInfo<T>, boolean, Map<String, List<String>>) - Constructor for class org.tribuo.common.tree.TreeModel
-
Constructs a trained decision tree model.
U
- useRandomSplitPoints - Variable in class org.tribuo.common.tree.AbstractCARTTrainer
-
Whether to choose split points for features at random.
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form