.. _l-ExtraTreeRegressor-~b-reg-64-default--o17: ExtraTreeRegressor - ~b-reg-64 - default - =========================================== Fitted on a problem type *~b-reg-64* (see :func:`find_suitable_problem `), method `predict` matches output . :: ExtraTreeRegressor(random_state=0) +-----------------------+----------+ | index | 0 | +=======================+==========+ | skl_nop | 1 | +-----------------------+----------+ | skl_nnodes | 223 | +-----------------------+----------+ | skl_ntrees | 1 | +-----------------------+----------+ | skl_max_depth | 14 | +-----------------------+----------+ | onx_size | 10835 | +-----------------------+----------+ | onx_nnodes | 2 | +-----------------------+----------+ | 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 | 1.13.1 | +-----------------------+----------+ | onx_ | 13 | +-----------------------+----------+ | onx_ai.onnx.ml | 3 | +-----------------------+----------+ | onx_op_Cast | 1 | +-----------------------+----------+ | onx_size_optim | 10835 | +-----------------------+----------+ | onx_nnodes_optim | 2 | +-----------------------+----------+ | onx_ninits_optim | 0 | +-----------------------+----------+ | fit_tree_.node_count | 223 | +-----------------------+----------+ | fit_tree_.leave_count | 112 | +-----------------------+----------+ | fit_tree_.max_depth | 14 | +-----------------------+----------+ .. gdot:: digraph{ size=7; ranksep=0.25; nodesep=0.05; orientation=portrait; X [shape=box color=red label="X\ndouble((0, 4))" fontsize=10]; variable [shape=box color=green label="variable\ndouble((0, 1))" fontsize=10]; tree_ensemble_cast [shape=box label="tree_ensemble_cast" fontsize=10]; TreeEnsembleRegressor [shape=box style="filled,rounded" color=orange label="TreeEnsembleRegressor\n(TreeEnsembleRegressor)\nn_targets=1\nnodes_falsenodeids=[ 62 9 4...\nnodes_featureids=[2 3 2 0 0 1 0...\nnodes_hitrates_as_tensor=[1. 1. 1. ...\nnodes_missing_value_tracks_true=[0 0 0 0 0...\nnodes_modes=[b'BRANCH_LEQ' b'BR...\nnodes_nodeids=[ 0 1 2 3 ...\nnodes_treeids=[0 0 0 0 0 0 0 0 ...\nnodes_truenodeids=[ 1 2 3 ...\nnodes_values_as_tensor=[1.8162294...\npost_transform=b'NONE'\ntarget_ids=[0 0 0 0 0 0 0 0 0 0...\ntarget_nodeids=[ 3 6 7 8...\ntarget_treeids=[0 0 0 0 0 0 0 0...\ntarget_weights_as_tensor=[0.14 0.28..." fontsize=10]; X -> TreeEnsembleRegressor; TreeEnsembleRegressor -> tree_ensemble_cast; tree_ensemble_cast [shape=box style="filled,rounded" color=orange label="Cast\n(tree_ensemble_cast)\nto=11" fontsize=10]; tree_ensemble_cast -> tree_ensemble_cast; tree_ensemble_cast -> variable; }