BernoulliNB - b-cl - default -#

Fitted on a problem type b-cl (see find_suitable_problem), method predict_proba matches output .

BernoulliNB()

index

0

skl_nop

1

skl_ncoef

1

skl_nlin

1

onx_size

1836

onx_nnodes

22

onx_ninits

9

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_

13

onx_ai.onnx.ml

1

onx_op_Cast

4

onx_op_ZipMap

1

onx_op_Reshape

2

onx_size_optim

1836

onx_nnodes_optim

22

onx_ninits_optim

9

fit_classes_.shape

2

fit_class_count_.shape

2

fit_feature_count_.shape

(2, 4)

fit_feature_log_prob_.shape

(2, 4)

fit_class_log_prior_.shape

2

fit_n_features_

4
%0 X X float((0, 4)) Greater Greater (Greater) X->Greater output_label output_label int64((0,)) output_probability output_probability [{int64, {'kind': 'tensor', 'elem': 'float', 'shape': }}] classes classes int32((2,)) [0 1] ArrayFeatureExtractor ArrayFeatureExtractor (ArrayFeatureExtractor) classes->ArrayFeatureExtractor feature_log_prob feature_log_prob float32((4, 2)) [[-0.02739897 -0.01273903] [-0.02739897 -0.01273903] [-0.02739897 -0.01273903] [-0.14518201 -0.01273903]] Exp Exp (Exp) feature_log_prob->Exp Sub1 Sub (Sub1) feature_log_prob->Sub1 class_log_prior class_log_prior float32((1, 2)) [[-1.1631508  -0.37469345]] Add2 Add (Add2) class_log_prior->Add2 constant constant float32(()) 1.0 Sub Sub (Sub) constant->Sub threshold threshold float32((1,)) [0.] threshold->Greater zero_tensor zero_tensor float32((1, 4)) [[0. 0. 0. 0.]] Add Add (Add) zero_tensor->Add axis axis int64((1,)) [0] ReduceSum ReduceSum (ReduceSum) axis->ReduceSum shape_tensor shape_tensor int64((2,)) [-1  1] Reshape Reshape (Reshape) shape_tensor->Reshape shape_tensor1 shape_tensor1 int64((1,)) [-1] Reshape1 Reshape (Reshape1) shape_tensor1->Reshape1 exp_result exp_result exp_result->Sub Exp->exp_result condition condition Cast Cast (Cast) to=1 condition->Cast Greater->condition cast_values cast_values cast_values->Add Cast->cast_values sub_result sub_result Log Log (Log) sub_result->Log Sub->sub_result binarised_input binarised_input MatMul MatMul (MatMul) binarised_input->MatMul Add->binarised_input neg_prob neg_prob neg_prob->ReduceSum neg_prob->Sub1 Log->neg_prob sum_neg_prob sum_neg_prob Add1 Add (Add1) sum_neg_prob->Add1 ReduceSum->sum_neg_prob difference_matrix difference_matrix difference_matrix->MatMul Sub1->difference_matrix dot_prod dot_prod dot_prod->Add1 MatMul->dot_prod partial_sum_result partial_sum_result partial_sum_result->Add2 Add1->partial_sum_result sum_result sum_result ArgMax ArgMax (ArgMax) axis=1 sum_result->ArgMax ReduceLogSumExp ReduceLogSumExp (ReduceLogSumExp) axes=[1] keepdims=0 sum_result->ReduceLogSumExp Sub2 Sub (Sub2) sum_result->Sub2 Add2->sum_result argmax_output argmax_output argmax_output->ArrayFeatureExtractor ArgMax->argmax_output reduce_log_sum_exp_result reduce_log_sum_exp_result reduce_log_sum_exp_result->Reshape ReduceLogSumExp->reduce_log_sum_exp_result reshaped_log_prob reshaped_log_prob reshaped_log_prob->Sub2 Reshape->reshaped_log_prob array_feature_extractor_result array_feature_extractor_result Cast1 Cast (Cast1) to=1 array_feature_extractor_result->Cast1 ArrayFeatureExtractor->array_feature_extractor_result cast2_result cast2_result cast2_result->Reshape1 Cast1->cast2_result log_prob log_prob Exp1 Exp (Exp1) log_prob->Exp1 Sub2->log_prob reshaped_result reshaped_result Cast2 Cast (Cast2) to=7 reshaped_result->Cast2 Reshape1->reshaped_result probabilities probabilities ZipMap ZipMap (ZipMap) classlabels_int64s=[0 1] probabilities->ZipMap Exp1->probabilities label label Cast3 Cast (Cast3) to=7 label->Cast3 Cast2->label ZipMap->output_probability Cast3->output_label

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