.. _l-SVR-b-reg-linear--o17:

SVR - b-reg - linear - 
=======================

Fitted on a problem type *b-reg*
(see :func:`find_suitable_problem
<mlprodict.onnxrt.validate.validate_problems.find_suitable_problem>`),
method `predict` matches output .


::

        SVR(kernel='linear')

+----------------------------+----------+
| index                      | 0        |
+============================+==========+
| skl_nop                    | 1        |
+----------------------------+----------+
| skl_ncoef                  | 1        |
+----------------------------+----------+
| skl_nlin                   | 1        |
+----------------------------+----------+
| onx_size                   | 2752     |
+----------------------------+----------+
| 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_                       | 9        |
+----------------------------+----------+
| onx_ai.onnx.ml             | 1        |
+----------------------------+----------+
| onx_op_Cast                | 1        |
+----------------------------+----------+
| onx_size_optim             | 2752     |
+----------------------------+----------+
| onx_nnodes_optim           | 2        |
+----------------------------+----------+
| onx_ninits_optim           | 0        |
+----------------------------+----------+
| fit_support_.shape         | 95       |
+----------------------------+----------+
| fit_support_vectors_.shape | (95, 4)  |
+----------------------------+----------+
| fit_dual_coef_.shape       | (1, 95)  |
+----------------------------+----------+
| fit_intercept_.shape       | 1        |
+----------------------------+----------+


.. gdot::

        digraph{
      size=7;
      ranksep=0.25;
      nodesep=0.05;
      orientation=portrait;

      X [shape=box color=red label="X\nfloat((0, 4))" fontsize=10];

      variable [shape=box color=green label="variable\nfloat((0, 1))" fontsize=10];


      SVM03 [shape=box label="SVM03" fontsize=10];
      SVM [shape=box style="filled,rounded" color=orange label="SVMRegressor\n(SVM)\ncoefficients=[ 1.         -1.  ...\nkernel_params=[0.06311981 0.   ...\nkernel_type=b'LINEAR'\nn_supports=95\npost_transform=b'NONE'\nrho=[0.15157957]\nsupport_vectors=[ 5.9683514e+00..." fontsize=10];
      X -> SVM;
      SVM -> SVM03;

      Cast [shape=box style="filled,rounded" color=orange label="Cast\n(Cast)\nto=1" fontsize=10];
      SVM03 -> Cast;
      Cast -> variable;
    }