ExtraTreeClassifier - ~m-label - default - {‘zipmap’: False}#

Fitted on a problem type ~m-label (see find_suitable_problem), method predict_proba matches output . Model was converted with additional parameter: <class 'sklearn.tree._classes.ExtraTreeClassifier'>={'zipmap': False}.

ExtraTreeClassifier(random_state=0)

index

0

skl_nop

1

skl_nnodes

127

skl_ntrees

1

skl_max_depth

13

onx_size

10411

onx_nnodes

23

onx_ninits

7

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_

15

onx_ai.onnx.ml

1

onx_op_Cast

2

onx_op_Reshape

7

onx_size_optim

10411

onx_nnodes_optim

23

onx_ninits_optim

7

fit_n_classes_.shape

3

fit_n_classes_

[2 2 2]

fit_n_features_

4

fit_tree_.node_count

127

fit_tree_.leave_count

64

fit_tree_.max_depth

13
%0 X X float((0, 4)) TreeEnsembleClassifier TreeEnsembleClassifier (TreeEnsembleClassifier) class_ids=[  5   7   9  11  13 ... class_nodeids=[  5   7   9  11 ... class_treeids=[0 0 0 0 0 0 0 0 ... class_weights=[1. 1. 1. 1. 1. 1... classlabels_int64s=[  0   1   2... nodes_falsenodeids=[ 32  23  22... nodes_featureids=[0 1 3 2 1 0 0... nodes_hitrates=[1. 1. 1. 1. 1. ... nodes_missing_value_tracks_true=[0 0 0 0 0... nodes_modes=[b'BRANCH_LEQ' b'BR... nodes_nodeids=[  0   1   2   3 ... nodes_treeids=[0 0 0 0 0 0 0 0 ... nodes_truenodeids=[  1   2   3 ... nodes_values=[5.384941  3.13197... post_transform=b'NONE' X->TreeEnsembleClassifier label label int64((0, 3)) probabilities probabilities float((3, 0, 2)) values values float32((3, 2, 127)) [[[69.  8.  8.  7.  0.  0.  0.  0.  0.  0.  0.  0.... ArrayFeatureExtractor ArrayFeatureExtractor (ArrayFeatureExtractor) values->ArrayFeatureExtractor shape_tensor shape_tensor int64((2,)) [ 1 -1] Reshape Reshape (Reshape) shape_tensor->Reshape Reshape1 Reshape (Reshape1) shape_tensor->Reshape1 Reshape3 Reshape (Reshape3) shape_tensor->Reshape3 Reshape5 Reshape (Reshape5) shape_tensor->Reshape5 k_column k_column int64(()) 0 ArrayFeatureExtractor1 ArrayFeatureExtractor (ArrayFeatureExtractor1) k_column->ArrayFeatureExtractor1 classes classes int64((2,)) [0 1] ArrayFeatureExtractor2 ArrayFeatureExtractor (ArrayFeatureExtractor2) classes->ArrayFeatureExtractor2 ArrayFeatureExtractor6 ArrayFeatureExtractor (ArrayFeatureExtractor6) classes->ArrayFeatureExtractor6 ArrayFeatureExtractor4 ArrayFeatureExtractor (ArrayFeatureExtractor4) classes->ArrayFeatureExtractor4 shape_tensor2 shape_tensor2 int64((2,)) [-1  1] Reshape2 Reshape (Reshape2) shape_tensor2->Reshape2 Reshape6 Reshape (Reshape6) shape_tensor2->Reshape6 Reshape4 Reshape (Reshape4) shape_tensor2->Reshape4 k_column1 k_column1 int64(()) 1 ArrayFeatureExtractor3 ArrayFeatureExtractor (ArrayFeatureExtractor3) k_column1->ArrayFeatureExtractor3 k_column2 k_column2 int64(()) 2 ArrayFeatureExtractor5 ArrayFeatureExtractor (ArrayFeatureExtractor5) k_column2->ArrayFeatureExtractor5 indices indices indices->Reshape dummy_proba dummy_proba TreeEnsembleClassifier->indices TreeEnsembleClassifier->dummy_proba reshaped_indices reshaped_indices reshaped_indices->ArrayFeatureExtractor Reshape->reshaped_indices out_indices out_indices Transpose Transpose (Transpose) perm=[0 2 1] out_indices->Transpose Transpose1 Transpose (Transpose1) perm=[2 1 0] out_indices->Transpose1 ArrayFeatureExtractor->out_indices proba_output proba_output Cast Cast (Cast) to=9 proba_output->Cast Transpose->proba_output transposed_result transposed_result transposed_result->ArrayFeatureExtractor1 transposed_result->ArrayFeatureExtractor3 transposed_result->ArrayFeatureExtractor5 Transpose1->transposed_result out_k_column out_k_column ArgMax ArgMax (ArgMax) axis=1 out_k_column->ArgMax ArrayFeatureExtractor1->out_k_column cast_result cast_result Cast1 Cast (Cast1) to=1 cast_result->Cast1 Cast->cast_result out_k_column1 out_k_column1 ArgMax1 ArgMax (ArgMax1) axis=1 out_k_column1->ArgMax1 ArrayFeatureExtractor3->out_k_column1 out_k_column2 out_k_column2 ArgMax2 ArgMax (ArgMax2) axis=1 out_k_column2->ArgMax2 ArrayFeatureExtractor5->out_k_column2 Cast1->probabilities argmax_output argmax_output argmax_output->Reshape1 ArgMax->argmax_output argmax_output1 argmax_output1 argmax_output1->Reshape3 ArgMax1->argmax_output1 argmax_output2 argmax_output2 argmax_output2->Reshape5 ArgMax2->argmax_output2 reshaped_result reshaped_result reshaped_result->ArrayFeatureExtractor2 Reshape1->reshaped_result reshaped_result1 reshaped_result1 reshaped_result1->ArrayFeatureExtractor4 Reshape3->reshaped_result1 reshaped_result2 reshaped_result2 reshaped_result2->ArrayFeatureExtractor6 Reshape5->reshaped_result2 preds preds preds->Reshape2 ArrayFeatureExtractor2->preds preds2 preds2 preds2->Reshape6 ArrayFeatureExtractor6->preds2 preds1 preds1 preds1->Reshape4 ArrayFeatureExtractor4->preds1 reshaped_preds reshaped_preds Concat Concat (Concat) axis=1 reshaped_preds->Concat Reshape2->reshaped_preds reshaped_preds2 reshaped_preds2 reshaped_preds2->Concat Reshape6->reshaped_preds2 reshaped_preds1 reshaped_preds1 reshaped_preds1->Concat Reshape4->reshaped_preds1 Concat->label

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