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tfdf.py_tree.node.LeafNode
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A leaf node i.e. the node containing a prediction/value/output.
Inherits From: AbstractNode
tfdf.py_tree.node.LeafNode(
value: tfdf.py_tree.node.AbstractValue,
leaf_idx: Optional[int] = None
)
Attributes |
|---|
leaf_idx
|
Index of the leaf in the tree in a depth first exploration.
|
value
|
|
Methods
pretty
View source
pretty(
prefix: str, is_pos: Optional[bool], depth: int, max_depth: Optional[int]
) -> str
Returns a recursive readable textual representation of a node.
| Args |
|---|
prefix
|
Prefix printed on the left side. Used to print the surrounding
edges.
|
is_pos
|
True/False if the node is a positive/negative child. None if the
node is a root.
|
depth
|
Depth of the node in the tree. There is no assuption of on the
depth of a root.
|
max_depth
|
Maximum depth for representation. Deeper nodes are skipped.
|
| Returns |
|---|
|
A pretty-string representing the node and its children.
|
scan_structure
View source
scan_structure(
conditions: tfdf.py_tree.node.ScanStructureAccumulator
)
Extracts the condition values and default evaluations.
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tfdf.py_tree.node.LeafNode\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/decision-forests/blob/main/tensorflow_decision_forests/component/py_tree/node.py#L168-L206) |\n\nA leaf node i.e. the node containing a prediction/value/output.\n\nInherits From: [`AbstractNode`](../../../tfdf/py_tree/node/AbstractNode) \n\n tfdf.py_tree.node.LeafNode(\n value: ../../../tfdf/py_tree/node/AbstractValue,\n leaf_idx: Optional[int] = None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|------------|-------------------------------------------------------------|\n| `leaf_idx` | Index of the leaf in the tree in a depth first exploration. |\n| `value` | \u003cbr /\u003e \u003cbr /\u003e |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `pretty`\n\n[View source](https://github.com/tensorflow/decision-forests/blob/main/tensorflow_decision_forests/component/py_tree/node.py#L196-L206) \n\n pretty(\n prefix: str, is_pos: Optional[bool], depth: int, max_depth: Optional[int]\n ) -\u003e str\n\nReturns a recursive readable textual representation of a node.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|-------------|----------------------------------------------------------------------------------|\n| `prefix` | Prefix printed on the left side. Used to print the surrounding edges. |\n| `is_pos` | True/False if the node is a positive/negative child. None if the node is a root. |\n| `depth` | Depth of the node in the tree. There is no assuption of on the depth of a root. |\n| `max_depth` | Maximum depth for representation. Deeper nodes are skipped. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A pretty-string representing the node and its children. ||\n\n\u003cbr /\u003e\n\n### `scan_structure`\n\n[View source](https://github.com/tensorflow/decision-forests/blob/main/tensorflow_decision_forests/component/py_tree/node.py#L134-L136) \n\n scan_structure(\n conditions: ../../../tfdf/py_tree/node/ScanStructureAccumulator\n )\n\nExtracts the condition values and default evaluations."]]
View source on GitHub