.. _op_ai_onnx_ml_SVMRegressor:

SVMRegressor
============

- **Domain**: ``ai.onnx.ml``
- **Since version**: 1

Support Vector Machine regression prediction and one-class SVM anomaly detection.

**Inputs**

- **X** (*T*): Data to be regressed.

**Outputs**

- **Y** (*tensor(float)*): Regression outputs (one score per target per example).

**Type Constraints**

- **T**: The input type must be a tensor of a numeric type, either [C] or [N,C].
  Allowed types: tensor(double), tensor(float), tensor(int32), tensor(int64).

Examples
--------

**test_cc_svmregressor_linear**

.. code-block:: text

    Node:
      ai.onnx.ml.SVMRegressor(x) -> (y)
      Attributes:
        kernel_type = "LINEAR"
        kernel_params = [0.0, 0.0, 0.0]
        support_vectors = [1.0, 0.0, 0.0, 1.0]
        coefficients = [2.0, -1.0]
        rho = [0.5]
        n_supports = 2
        post_transform = "NONE"

.. code-block:: text

    Inputs:
      x: shape=(2, 2), dtype=float32
        [[3., 1.],
         [0., 2.]]

    Outputs:
      y: shape=(2, 1), dtype=float32
        [[ 5.5],
         [-1.5]]