HistGradientBoostingRegressor - ~b-reg-64 - default -#

Fitted on a problem type ~b-reg-64 (see find_suitable_problem), method predict matches output .

HistGradientBoostingRegressor(random_state=0)

index

0

skl_nop

1

onx_size

32964

onx_nnodes

1

onx_ninits

0

onx_doc_string

onx_ir_version

8

onx_domain

ai.onnx

onx_model_version

0

onx_producer_name

skl2onnx

onx_producer_version

1.11.1

onx_mlprodict

1

onx_

15

onx_size_optim

32964

onx_nnodes_optim

1

onx_ninits_optim

0

fit_train_score_.shape

0

fit_validation_score_.shape

0

fit__predictors.size

100

fit__predictors.sum|tree_.leave_count

412

fit__predictors.sum|tree_.node_count

724

fit__predictors.max|tree_.max_depth

4

%0 X X double((0, 4)) TreeEnsembleRegressorDouble TreeEnsembleRegressorDouble (TreeEnsembleRegressorDouble) base_values=[1.78866071] n_targets=1 nodes_falsenodeids=[2 0 4 0 0 2... nodes_featureids=[2 0 2 0 0 2 0... nodes_hitrates=[1. 1. 1. 1. 1. ... nodes_missing_value_tracks_true=[0 0 1 0 0... nodes_modes=[b'BRANCH_LEQ' b'LE... nodes_nodeids=[0 1 2 3 4 0 1 2 ... nodes_treeids=[ 0  0  0  0  0  ... nodes_truenodeids=[1 0 3 0 0 1 ... nodes_values=[2.54898403 0.    ... post_transform=b'NONE' target_ids=[0 0 0 0 0 0 0 0 0 0... target_nodeids=[1 3 4 1 3 4 1 3... target_treeids=[ 0  0  0  1  1 ... target_weights=[-1.54494643e-01... X->TreeEnsembleRegressorDouble variable variable double((0, 1)) TreeEnsembleRegressorDouble->variable