.. _l-LassoLarsIC-b-reg-default--o17:

LassoLarsIC - b-reg - default - 
================================

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


::

        LassoLarsIC()

+---------------------------+----------+
| index                     | 0        |
+===========================+==========+
| skl_nop                   | 1        |
+---------------------------+----------+
| skl_ncoef                 | 4        |
+---------------------------+----------+
| skl_nlin                  | 1        |
+---------------------------+----------+
| onx_size                  | 254      |
+---------------------------+----------+
| onx_nnodes                | 1        |
+---------------------------+----------+
| 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_ai.onnx.ml            | 1        |
+---------------------------+----------+
| onx_                      | 17       |
+---------------------------+----------+
| onx_size_optim            | 254      |
+---------------------------+----------+
| onx_nnodes_optim          | 1        |
+---------------------------+----------+
| onx_ninits_optim          | 0        |
+---------------------------+----------+
| fit_alphas_.shape         | 5        |
+---------------------------+----------+
| fit_noise_variance_.shape | 1        |
+---------------------------+----------+
| fit_criterion_.shape      | 5        |
+---------------------------+----------+
| fit_coef_.shape           | 4        |
+---------------------------+----------+


.. 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];


      LinearRegressor [shape=box style="filled,rounded" color=orange label="LinearRegressor\n(LinearRegressor)\ncoefficients=[-0.14164856  0.  ...\nintercepts=[0.1103766]" fontsize=10];
      X -> LinearRegressor;
      LinearRegressor -> variable;
    }