.. _l-IncrementalPCA-num-tr-default--o17:

IncrementalPCA - num-tr - default - 
====================================

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


::

        IncrementalPCA()

+-------------------------------------+----------+
| index                               | 0        |
+=====================================+==========+
| skl_nop                             | 1        |
+-------------------------------------+----------+
| onx_size                            | 336      |
+-------------------------------------+----------+
| onx_nnodes                          | 2        |
+-------------------------------------+----------+
| 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_size_optim                      | 336      |
+-------------------------------------+----------+
| onx_nnodes_optim                    | 2        |
+-------------------------------------+----------+
| onx_ninits_optim                    | 2        |
+-------------------------------------+----------+
| fit_components_.shape               | (4, 4)   |
+-------------------------------------+----------+
| fit_mean_.shape                     | 4        |
+-------------------------------------+----------+
| fit_var_.shape                      | 4        |
+-------------------------------------+----------+
| fit_singular_values_.shape          | 4        |
+-------------------------------------+----------+
| fit_explained_variance_.shape       | 4        |
+-------------------------------------+----------+
| fit_explained_variance_ratio_.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, 4))" fontsize=10];

      transform_matrix [shape=box label="transform_matrix\nfloat32((4, 4))\n[[ 0.35053724  0.6425043  -0.54678947  0.40661186]..." fontsize=10];
      mean [shape=box label="mean\nfloat32((4,))\n[5.860339 2.997882 3.759892 1.188384]" fontsize=10];

      sub_result [shape=box label="sub_result" fontsize=10];
      Sub [shape=box style="filled,rounded" color=orange label="Sub\n(Sub)" fontsize=10];
      X -> Sub;
      mean -> Sub;
      Sub -> sub_result;

      MatMul [shape=box style="filled,rounded" color=orange label="MatMul\n(MatMul)" fontsize=10];
      sub_result -> MatMul;
      transform_matrix -> MatMul;
      MatMul -> variable;
    }