tfdf.builder.GradientBoostedTreeBuilder

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Gradient Boosted Tree model builder.

Inherits From: AbstractDecisionForestBuilder, AbstractBuilder

tfdf.builder.GradientBoostedTreeBuilder(
    path: str,
    objective: tfdf.py_tree.objective.AbstractObjective,
    bias: Optional[float] = 0.0,
    model_format: Optional[tfdf.builder.ModelFormat] = tfdf.builder.ModelFormat.TENSORFLOW_SAVED_MODEL,
    import_dataspec: Optional[data_spec_pb2.DataSpecification] = None,
    input_signature_example_fn: Optional[tf_core.InputModelSignatureFn] = tfdf.keras.build_default_input_model_signature,
    file_prefix: Optional[str] = None,
    verbose: int = 1,
    advanced_arguments: Optional[tfdf.builder.AdvancedArguments] = None
)

Attributes
dataspec	Dataspec, possibly partially constructed. Can be called before close for advanced model edition.
objective	Objective of the model.

Methods

add_tree

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add_tree(
    tree: tfdf.py_tree.tree.Tree
)

Adds one tree to the model.

check_leaf

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check_leaf(
    node: tfdf.py_tree.node.LeafNode
)

Called on all the leaf nodes during the export.

check_non_leaf

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check_non_leaf(
    node: tfdf.py_tree.node.NonLeafNode
)

Called on all the non-leaf nodes during the export.

close

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close()

Finalize the builder work.

This method should be called last.

get_dictionary

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get_dictionary(
    col_name: str
) -> List[str]

Gets the dictionary of a categorical(-set) string feature.

model_type

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model_type() -> str

Unique key describing the type of the model.

observe_feature

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observe_feature(
    feature: tfdf.inspector.SimpleColumnSpec,
    categorical_values: Optional[Union[List[str], List[int]]] = None
)

Register a feature and some of its possible value.

Generally, users don't need to call this function. An example of advanced exception is if a model does not refer to a specific possible categorical value, and if this value should be treated differently than out-of-vocabulary values.

Should be called at least once on each of the model input features. If called multiple times with categorical_values the set of possible values will be the union of the categorical_valuess.

Args
feature	Definition of the feature.
categorical_values	Set of observed values. Only for categorical-like features.

set_dictionary

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set_dictionary(
    col_name: str, dictionary: List[str]
) -> None

Sets the dictionary of a categorical or categorical-set column.

specialized_header

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specialized_header() -> Any

Gets the specialized header of the model.

specialized_header_filename

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specialized_header_filename() -> str

Gets the filename of the specialized header.

yggdrasil_model_path

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yggdrasil_model_path()

Gets the path to the destination yggdrasil model.