.. _l-GaussianProcessRegressor-~b-reg-NSV-64-expsine-cdist-o17: GaussianProcessRegressor - ~b-reg-NSV-64 - expsine - cdist ========================================================== Fitted on a problem type *~b-reg-NSV-64* (see :func:`find_suitable_problem `), method `predict` matches output . Model was converted with additional parameter: ``={'optim': 'cdist'}``. :: GaussianProcessRegressor(alpha=20.0, kernel=ExpSineSquared(length_scale=1, periodicity=1), random_state=0) +------------------------------------------+------------+ | index | 0 | +==========================================+============+ | skl_nop | 1 | +------------------------------------------+------------+ | onx_size | 5512 | +------------------------------------------+------------+ | onx_nnodes | 11 | +------------------------------------------+------------+ | 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 | 1.13.1 | +------------------------------------------+------------+ | onx_ | 16 | +------------------------------------------+------------+ | onx_com.microsoft | 1 | +------------------------------------------+------------+ | onx_op_Reshape | 1 | +------------------------------------------+------------+ | onx_size_optim | 5512 | +------------------------------------------+------------+ | onx_nnodes_optim | 11 | +------------------------------------------+------------+ | onx_ninits_optim | 9 | +------------------------------------------+------------+ | fit_X_train_.shape | (112, 4) | +------------------------------------------+------------+ | fit_y_train_.shape | 112 | +------------------------------------------+------------+ | fit_log_marginal_likelihood_value_.shape | 1 | +------------------------------------------+------------+ | fit_L_.shape | (112, 112) | +------------------------------------------+------------+ | fit_alpha_.shape | 112 | +------------------------------------------+------------+ .. gdot:: digraph{ size=7; ranksep=0.25; nodesep=0.05; orientation=portrait; X [shape=box color=red label="X\ndouble((0, 0))" fontsize=10]; GPmean [shape=box color=green label="GPmean\ndouble((0, 1))" fontsize=10]; kgpd_CDistcst [shape=box label="kgpd_CDistcst\nfloat64((112, 4))\n[[ 4.30175021e+00 3.94531870e+00 9.21953113e-01 ..." fontsize=10]; kgpd_Divcst [shape=box label="kgpd_Divcst\nfloat64((1,))\n[7400.40025467]" fontsize=10]; kgpd_Mulcst [shape=box label="kgpd_Mulcst\nfloat64((1,))\n[3.14159265]" fontsize=10]; kgpd_Divcst1 [shape=box label="kgpd_Divcst1\nfloat64((1,))\n[0.00318648]" fontsize=10]; kgpd_Powcst [shape=box label="kgpd_Powcst\nfloat64((1,))\n[2.]" fontsize=10]; kgpd_Mulcst1 [shape=box label="kgpd_Mulcst1\nfloat64((1,))\n[-2.]" fontsize=10]; gpr_MatMulcst [shape=box label="gpr_MatMulcst\nfloat64((112,))\n[-0.01557005 -0.01321393 0.07640723 -0.00190292 -..." fontsize=10]; gpr_Addcst [shape=box label="gpr_Addcst\nfloat64((1, 1))\n[[0.]]" fontsize=10]; Re_Reshapecst [shape=box label="Re_Reshapecst\nint64((2,))\n[-1 1]" fontsize=10]; kgpd_dist [shape=box label="kgpd_dist" fontsize=10]; kgpd_CDist [shape=box style="filled,rounded" color=orange label="CDist\n(kgpd_CDist)\nmetric=b'euclidean'" fontsize=10]; X -> kgpd_CDist; kgpd_CDistcst -> kgpd_CDist; kgpd_CDist -> kgpd_dist; kgpd_C03 [shape=box label="kgpd_C03" fontsize=10]; kgpd_Div [shape=box style="filled,rounded" color=orange label="Div\n(kgpd_Div)" fontsize=10]; kgpd_dist -> kgpd_Div; kgpd_Divcst -> kgpd_Div; kgpd_Div -> kgpd_C03; kgpd_C02 [shape=box label="kgpd_C02" fontsize=10]; kgpd_Mul [shape=box style="filled,rounded" color=orange label="Mul\n(kgpd_Mul)" fontsize=10]; kgpd_C03 -> kgpd_Mul; kgpd_Mulcst -> kgpd_Mul; kgpd_Mul -> kgpd_C02; kgpd_output02 [shape=box label="kgpd_output02" fontsize=10]; kgpd_Sin [shape=box style="filled,rounded" color=orange label="Sin\n(kgpd_Sin)" fontsize=10]; kgpd_C02 -> kgpd_Sin; kgpd_Sin -> kgpd_output02; kgpd_C01 [shape=box label="kgpd_C01" fontsize=10]; kgpd_Div1 [shape=box style="filled,rounded" color=orange label="Div\n(kgpd_Div1)" fontsize=10]; kgpd_output02 -> kgpd_Div1; kgpd_Divcst1 -> kgpd_Div1; kgpd_Div1 -> kgpd_C01; kgpd_Z0 [shape=box label="kgpd_Z0" fontsize=10]; kgpd_Pow [shape=box style="filled,rounded" color=orange label="Pow\n(kgpd_Pow)" fontsize=10]; kgpd_C01 -> kgpd_Pow; kgpd_Powcst -> kgpd_Pow; kgpd_Pow -> kgpd_Z0; kgpd_C0 [shape=box label="kgpd_C0" fontsize=10]; kgpd_Mul1 [shape=box style="filled,rounded" color=orange label="Mul\n(kgpd_Mul1)" fontsize=10]; kgpd_Z0 -> kgpd_Mul1; kgpd_Mulcst1 -> kgpd_Mul1; kgpd_Mul1 -> kgpd_C0; kgpd_output01 [shape=box label="kgpd_output01" fontsize=10]; kgpd_Exp [shape=box style="filled,rounded" color=orange label="Exp\n(kgpd_Exp)" fontsize=10]; kgpd_C0 -> kgpd_Exp; kgpd_Exp -> kgpd_output01; gpr_Y0 [shape=box label="gpr_Y0" fontsize=10]; gpr_MatMul [shape=box style="filled,rounded" color=orange label="MatMul\n(gpr_MatMul)" fontsize=10]; kgpd_output01 -> gpr_MatMul; gpr_MatMulcst -> gpr_MatMul; gpr_MatMul -> gpr_Y0; gpr_C0 [shape=box label="gpr_C0" fontsize=10]; gpr_Add [shape=box style="filled,rounded" color=orange label="Add\n(gpr_Add)" fontsize=10]; gpr_Y0 -> gpr_Add; gpr_Addcst -> gpr_Add; gpr_Add -> gpr_C0; Re_Reshape [shape=box style="filled,rounded" color=orange label="Reshape\n(Re_Reshape)\nallowzero=0" fontsize=10]; gpr_C0 -> Re_Reshape; Re_Reshapecst -> Re_Reshape; Re_Reshape -> GPmean; }