.. _l-SGDOneClassSVM-outlier-default--o17:

SGDOneClassSVM - outlier - default - 
=====================================

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


::

        SGDOneClassSVM(random_state=0)

+----------------------+----------+
| index                | 0        |
+======================+==========+
| skl_nop              | 1        |
+----------------------+----------+
| skl_ncoef            | 4        |
+----------------------+----------+
| skl_nlin             | 1        |
+----------------------+----------+
| onx_size             | 363      |
+----------------------+----------+
| onx_nnodes           | 4        |
+----------------------+----------+
| onx_ninits           | 2        |
+----------------------+----------+
| 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_                 | 13       |
+----------------------+----------+
| onx_op_Cast          | 1        |
+----------------------+----------+
| onx_size_optim       | 363      |
+----------------------+----------+
| onx_nnodes_optim     | 4        |
+----------------------+----------+
| onx_ninits_optim     | 2        |
+----------------------+----------+
| fit_coef_.shape      | 4        |
+----------------------+----------+
| fit_offset_.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];

      label [shape=box color=green label="label\nint64((0,))" fontsize=10];
      scores [shape=box color=green label="scores\nfloat((0,))" fontsize=10];

      coef [shape=box label="coef\nfloat32((4,))\n[1.2899065  0.7942635  0.39049125 0.14721905]" fontsize=10];
      offset [shape=box label="offset\nfloat32((1,))\n[9.148465]" fontsize=10];

      matmul_result [shape=box label="matmul_result" fontsize=10];
      MatMul [shape=box style="filled,rounded" color=orange label="MatMul\n(MatMul)" fontsize=10];
      X -> MatMul;
      coef -> MatMul;
      MatMul -> matmul_result;

      Sub [shape=box style="filled,rounded" color=orange label="Sub\n(Sub)" fontsize=10];
      matmul_result -> Sub;
      offset -> Sub;
      Sub -> scores;

      class_prediction [shape=box label="class_prediction" fontsize=10];
      N2 [shape=box style="filled,rounded" color=orange label="Sign\n(N2)" fontsize=10];
      scores -> N2;
      N2 -> class_prediction;

      Cast [shape=box style="filled,rounded" color=orange label="Cast\n(Cast)\nto=7" fontsize=10];
      class_prediction -> Cast;
      Cast -> label;
    }