Functions
int	TreeliteGetModelBuilder (char const json_str, TreeliteModelBuilderHandle out)
	Initialize a model builder object from a JSON string. More...

int	TreeliteDeleteModelBuilder (TreeliteModelBuilderHandle model_builder)
	Delete model builder object from memory. More...

int	TreeliteModelBuilderStartTree (TreeliteModelBuilderHandle model_builder)
	Start a new tree. More...

int	TreeliteModelBuilderEndTree (TreeliteModelBuilderHandle model_builder)
	End the current tree. More...

int	TreeliteModelBuilderStartNode (TreeliteModelBuilderHandle model_builder, int node_key)
	Start a new node. More...

int	TreeliteModelBuilderEndNode (TreeliteModelBuilderHandle model_builder)
	End the current node. More...

int	TreeliteModelBuilderNumericalTest (TreeliteModelBuilderHandle model_builder, int32_t split_index, double threshold, int default_left, char const *cmp, int left_child_key, int right_child_key)
	Declare the current node as a numerical test node, where the test is of form [feature value] [cmp] [threshold]. Data points for which the test evaluates to True will be mapped to the left child node; all other data points (for which the test evaluates to False) will be mapped to the right child node. More...

int	TreeliteModelBuilderCategoricalTest (TreeliteModelBuilderHandle model_builder, int32_t split_index, int default_left, uint32_t const *category_list, size_t category_list_len, int category_list_right_child, int left_child_key, int right_child_key)
	Declare the current node as a categorical test node, where the test is of form [feature value] \in [category list]. More...

int	TreeliteModelBuilderLeafScalar (TreeliteModelBuilderHandle model_builder, double leaf_value)
	Declare the current node as a leaf node with a scalar output. More...

int	TreeliteModelBuilderLeafVectorFloat32 (TreeliteModelBuilderHandle model_builder, float const *leaf_vector, size_t leaf_vector_len)
	Declare the current node as a leaf node with a vector output (float32) More...

int	TreeliteModelBuilderLeafVectorFloat64 (TreeliteModelBuilderHandle model_builder, double const *leaf_vector, size_t leaf_vector_len)
	Declare the current node as a leaf node with a vector output (float64) More...

int	TreeliteModelBuilderGain (TreeliteModelBuilderHandle model_builder, double gain)
	Specify the gain (loss reduction) that's resulted from the current split. More...

int	TreeliteModelBuilderDataCount (TreeliteModelBuilderHandle model_builder, uint64_t data_count)
	Specify the number of data points (samples) that are mapped to the current node. More...

int	TreeliteModelBuilderSumHess (TreeliteModelBuilderHandle model_builder, double sum_hess)
	Specify the weighted sample count or the sum of Hessians for the data points that are mapped to the current node. More...

int	TreeliteModelBuilderCommitModel (TreeliteModelBuilderHandle model_builder, TreeliteModelHandle *out)
	Conclude model building and obtain the final model object. More...

Detailed Description

Function Documentation

◆ TreeliteDeleteModelBuilder()

int TreeliteDeleteModelBuilder ( TreeliteModelBuilderHandle model_builder )

Delete model builder object from memory.

Parameters

model_builder Model builder object to be deleted

Returns: 0 for success, -1 for failure

◆ TreeliteGetModelBuilder()

int TreeliteGetModelBuilder	(	char const *	json_str,
		TreeliteModelBuilderHandle *	out
	)

Initialize a model builder object from a JSON string.

The JSON string must contain all relevant metadata, including:

threshold_type: Type of thresholds in the tree model
leaf_output_type: Type of leaf outputs in the tree model
metadata: Model metadata, consisting of following subfields:
- num_feature: Number of features
- task_type: Task type
- average_tree_output: Whether to average outputs of trees
- num_target: Number of targets
- num_class: Number of classes. num_class[i] is the number of classes of target i.
- leaf_vector_shape: Shape of the output from each leaf node
tree_annotation: Annotation for individual trees, consisting of following subfields:
- num_tree: Number of trees
- target_id: target_id Target that each tree is associated with
- class_id: Class that each tree is associated with
postprocessor: Postprocessor for prediction outputs, consisting of following subfields:
- name: Name of postprocessor
- config_json: Optional JSON string to configure the postprocessor
base_scores: Baseline scores for targets and classes, before adding tree outputs. Also known as the intercept.
attributes: Arbitrary JSON object, to be stored in the "attributes" field in the model object.

Parameters

json_str	JSON string containing relevant metadata.
out	Model builder object

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderCategoricalTest()

int TreeliteModelBuilderCategoricalTest	(	TreeliteModelBuilderHandle	model_builder,
		int32_t	split_index,
		int	default_left,
		uint32_t const *	category_list,
		size_t	category_list_len,
		int	category_list_right_child,
		int	left_child_key,
		int	right_child_key
	)

Declare the current node as a categorical test node, where the test is of form [feature value] \in [category list].

Parameters

model_builder	Model builder object
split_index	Feature ID
default_left	Whether the missing value should be mapped to the left child
category_list	List of categories to be tested for match
category_list_len	Length of category_list
category_list_right_child	Whether the data points for which the test evaluates to True should be mapped to the right child or the left child.
left_child_key	Integer key that unique identifies the left child node.
right_child_key	Integer key that unique identifies the right child node.

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderCommitModel()

int TreeliteModelBuilderCommitModel	(	TreeliteModelBuilderHandle	model_builder,
		TreeliteModelHandle *	out
	)

Conclude model building and obtain the final model object.

Parameters

model_builder	Model builder object
out	Final model object

◆ TreeliteModelBuilderDataCount()

int TreeliteModelBuilderDataCount	(	TreeliteModelBuilderHandle	model_builder,
		uint64_t	data_count
	)

Specify the number of data points (samples) that are mapped to the current node.

Parameters

model_builder	Model builder object
data_count	Number of data points

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderEndNode()

int TreeliteModelBuilderEndNode ( TreeliteModelBuilderHandle model_builder )

End the current node.

Parameters

model_builder Model builder object

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderEndTree()

int TreeliteModelBuilderEndTree ( TreeliteModelBuilderHandle model_builder )

End the current tree.

Parameters

model_builder Model builder object

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderGain()

int TreeliteModelBuilderGain	(	TreeliteModelBuilderHandle	model_builder,
		double	gain
	)

Specify the gain (loss reduction) that's resulted from the current split.

Parameters

model_builder	Model builder object
gain	Gain (loss reduction)

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderLeafScalar()

int TreeliteModelBuilderLeafScalar	(	TreeliteModelBuilderHandle	model_builder,
		double	leaf_value
	)

Declare the current node as a leaf node with a scalar output.

Parameters

model_builder	Model builder object
leaf_value	Value of leaf output

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderLeafVectorFloat32()

int TreeliteModelBuilderLeafVectorFloat32	(	TreeliteModelBuilderHandle	model_builder,
		float const *	leaf_vector,
		size_t	leaf_vector_len
	)

Declare the current node as a leaf node with a vector output (float32)

Parameters

model_builder	Model builder object
leaf_vector	Value of leaf output
leaf_vector_len	Length of leaf_vector

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderLeafVectorFloat64()

int TreeliteModelBuilderLeafVectorFloat64	(	TreeliteModelBuilderHandle	model_builder,
		double const *	leaf_vector,
		size_t	leaf_vector_len
	)

Declare the current node as a leaf node with a vector output (float64)

Parameters

model_builder	Model builder object
leaf_vector	Value of leaf output
leaf_vector_len	Length of leaf_vector

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderNumericalTest()

int TreeliteModelBuilderNumericalTest	(	TreeliteModelBuilderHandle	model_builder,
		int32_t	split_index,
		double	threshold,
		int	default_left,
		char const *	cmp,
		int	left_child_key,
		int	right_child_key
	)

Declare the current node as a numerical test node, where the test is of form [feature value] [cmp] [threshold]. Data points for which the test evaluates to True will be mapped to the left child node; all other data points (for which the test evaluates to False) will be mapped to the right child node.

Parameters

model_builder	Model builder object
split_index	Feature ID
threshold	Threshold
default_left	Whether the missing value should be mapped to the left child
cmp	Comparison operator
left_child_key	Integer key that unique identifies the left child node.
right_child_key	Integer key that unique identifies the right child node.

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderStartNode()

int TreeliteModelBuilderStartNode	(	TreeliteModelBuilderHandle	model_builder,
		int	node_key
	)

Start a new node.

Parameters

model_builder	Model builder object
node_key	Integer key that unique identifies the node.

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderStartTree()

int TreeliteModelBuilderStartTree ( TreeliteModelBuilderHandle model_builder )

Start a new tree.

Parameters

model_builder Model builder object

Returns: 0 for success, -1 for failure

◆ TreeliteModelBuilderSumHess()

int TreeliteModelBuilderSumHess	(	TreeliteModelBuilderHandle	model_builder,
		double	sum_hess
	)

Specify the weighted sample count or the sum of Hessians for the data points that are mapped to the current node.

Parameters

model_builder	Model builder object
sum_hess	Weighted sample count or the sum of Hessians

Returns: 0 for success, -1 for failure

Functions

Detailed Description

Function Documentation

◆ TreeliteDeleteModelBuilder()

◆ TreeliteGetModelBuilder()

◆ TreeliteModelBuilderCategoricalTest()

◆ TreeliteModelBuilderCommitModel()

◆ TreeliteModelBuilderDataCount()

◆ TreeliteModelBuilderEndNode()

◆ TreeliteModelBuilderEndTree()

◆ TreeliteModelBuilderGain()

◆ TreeliteModelBuilderLeafScalar()

◆ TreeliteModelBuilderLeafVectorFloat32()

◆ TreeliteModelBuilderLeafVectorFloat64()

◆ TreeliteModelBuilderNumericalTest()

◆ TreeliteModelBuilderStartNode()

◆ TreeliteModelBuilderStartTree()

◆ TreeliteModelBuilderSumHess()