RANSACRegressor - ~m-reg-64 - default -#

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

RANSACRegressor(random_state=0)

index

0

skl_nop

1

onx_size

442

onx_nnodes

4

onx_ninits

3

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_

14

onx_op_Identity

1

onx_op_Reshape

1

onx_size_optim

404

onx_nnodes_optim

3

onx_ninits_optim

3

fit_inlier_mask_.shape

112
%0 X X double((0, 4)) MatMul MatMul (MatMul) X->MatMul variable variable double((0, 1)) coef coef float64((4, 2)) [[-0.59725381 -0.59725381] [ 0.11190388  0.11190388] [ 0.706316    0.706316  ] [ 0.4595337   0.4595337 ]] coef->MatMul intercept intercept float64((2,)) [1.85268469 2.35268469] Add Add (Add) intercept->Add shape_tensor shape_tensor int64((2,)) [-1  2] Reshape Reshape (Reshape) shape_tensor->Reshape multiplied multiplied multiplied->Add MatMul->multiplied resh resh resh->Reshape Add->resh label label Identity Identity (Identity) label->Identity Reshape->label Identity->variable

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