module `onnxrt.ops_cpu.op_tree_ensemble_classifier_`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_

Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc in onnxruntime.

source on GitHub

Classes#

class	truncated documentation
`RuntimeTreeEnsembleClassifierDouble`	Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc …
`RuntimeTreeEnsembleClassifierFloat`	Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc …

Properties#

property	truncated documentation
`base_values_`	See lpyort-TreeEnsembleClassifier.
`base_values_`	See lpyort-TreeEnsembleClassifier.
`class_count_`	See lpyort-TreeEnsembleClassifier.
`class_count_`	See lpyort-TreeEnsembleClassifier.
`class_ids_`	See lpyort-TreeEnsembleClassifier.
`class_ids_`	See lpyort-TreeEnsembleClassifier.
`class_nodeids_`	See lpyort-TreeEnsembleClassifier.
`class_nodeids_`	See lpyort-TreeEnsembleClassifier.
`class_treeids_`	See lpyort-TreeEnsembleClassifier.
`class_treeids_`	See lpyort-TreeEnsembleClassifier.
`class_weights_`	See lpyort-TreeEnsembleClassifier.
`class_weights_`	See lpyort-TreeEnsembleClassifier.
`classlabels_int64s_`	See lpyort-TreeEnsembleClassifier.
`classlabels_int64s_`	See lpyort-TreeEnsembleClassifier.
`consecutive_leaf_data_`	Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).
`consecutive_leaf_data_`	Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).
`missing_tracks_true_`	See lpyort-TreeEnsembleClassifier.
`missing_tracks_true_`	See lpyort-TreeEnsembleClassifier.
`nodes_falsenodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_falsenodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_featureids_`	See lpyort-TreeEnsembleClassifier.
`nodes_featureids_`	See lpyort-TreeEnsembleClassifier.
`nodes_hitrates_`	See lpyort-TreeEnsembleClassifier.
`nodes_hitrates_`	See lpyort-TreeEnsembleClassifier.
`nodes_modes_`
`nodes_modes_`
`nodes_nodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_nodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_treeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_treeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_truenodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_truenodeids_`	See lpyort-TreeEnsembleClassifier.
`nodes_values_`	See lpyort-TreeEnsembleClassifier.
`nodes_values_`	See lpyort-TreeEnsembleClassifier.
`post_transform_`	See lpyort-TreeEnsembleClassifier.
`post_transform_`	See lpyort-TreeEnsembleClassifier.
`roots_`	Returns the roots indices.
`roots_`	Returns the roots indices.
`same_mode_`	Tells if all nodes applies the same rule for thresholds.
`same_mode_`	Tells if all nodes applies the same rule for thresholds.

Documentation#

Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc in onnxruntime.

class mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble)#

Bases: pybind11_object

Implements runtime for operator TreeEnsembleClassifier. The code is inspired from tree_ensemble_classifier.cc in onnxruntime. Supports double only.

__init__(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble) → None#

property base_values_#: See lpyort-TreeEnsembleClassifier.

property class_count_#: See lpyort-TreeEnsembleClassifier.

property class_ids_#: See lpyort-TreeEnsembleClassifier.

property class_nodeids_#: See lpyort-TreeEnsembleClassifier.

property class_treeids_#: See lpyort-TreeEnsembleClassifier.

property class_weights_#: See lpyort-TreeEnsembleClassifier.

property classlabels_int64s_#: See lpyort-TreeEnsembleClassifier.

compute(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble, arg0: numpy.ndarray[numpy.float64]) → tuple#: Computes the predictions for the random forest.

property consecutive_leaf_data_#: Tells if there are two consecutive targets sharing the same node and the same tree (it should not happen in 1D target).

init(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble, arg0: numpy.ndarray[numpy.float64], arg1: numpy.ndarray[numpy.int64], arg2: numpy.ndarray[numpy.int64], arg3: numpy.ndarray[numpy.int64], arg4: numpy.ndarray[numpy.float64], arg5: numpy.ndarray[numpy.int64], arg6: List[str], arg7: numpy.ndarray[numpy.int64], arg8: numpy.ndarray[numpy.int64], arg9: numpy.ndarray[numpy.float64], arg10: numpy.ndarray[numpy.int64], arg11: List[str], arg12: numpy.ndarray[numpy.int64], arg13: numpy.ndarray[numpy.int64], arg14: numpy.ndarray[numpy.int64], arg15: numpy.ndarray[numpy.float64], arg16: str) → None#: Initializes the runtime with the ONNX attributes in alphabetical order.

property missing_tracks_true_#: See lpyort-TreeEnsembleClassifier.

property nodes_falsenodeids_#: See lpyort-TreeEnsembleClassifier.

property nodes_featureids_#: See lpyort-TreeEnsembleClassifier.

property nodes_hitrates_#: See lpyort-TreeEnsembleClassifier.

property nodes_nodeids_#: See lpyort-TreeEnsembleClassifier.

property nodes_treeids_#: See lpyort-TreeEnsembleClassifier.

property nodes_truenodeids_#: See lpyort-TreeEnsembleClassifier.

property nodes_values_#: See lpyort-TreeEnsembleClassifier.

omp_get_max_threads(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble) → int#: Returns omp_get_max_threads from openmp library.

property post_transform_#: See lpyort-TreeEnsembleClassifier.

property roots_#: Returns the roots indices.

runtime_options(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierDouble) → str#: Returns indications about how the runtime was compiled.

property same_mode_#: Tells if all nodes applies the same rule for thresholds.

class mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierFloat(self: mlprodict.onnxrt.ops_cpu.op_tree_ensemble_classifier_.RuntimeTreeEnsembleClassifierFloat)#