ai.onnx.ml - SVMRegressor#

SVMRegressor - 1#

Version

  • name: SVMRegressor (GitHub)

  • domain: ai.onnx.ml

  • since_version: 1

  • function:

  • support_level: SupportType.COMMON

  • shape inference: False

This version of the operator has been available since version 1 of domain ai.onnx.ml.

Summary

Attributes

  • coefficients - FLOATS : Support vector coefficients.

  • kernel_params - FLOATS : List of 3 elements containing gamma, coef0, and degree, in that order. Zero if unused for the kernel.

  • kernel_type - STRING : The kernel type, one of ‘LINEAR,’ ‘POLY,’ ‘RBF,’ ‘SIGMOID’.

  • n_supports - INT : The number of support vectors.

  • one_class - INT : Flag indicating whether the regression is a one-class SVM or not.

  • post_transform - STRING : Indicates the transform to apply to the score. <br>One of ‘NONE,’ ‘SOFTMAX,’ ‘LOGISTIC,’ ‘SOFTMAX_ZERO,’ or ‘PROBIT.’

  • rho - FLOATS :

  • support_vectors - FLOATS : Chosen support vectors

Inputs

  • X (heterogeneous) - T:

Outputs

  • Y (heterogeneous) - tensor(float):

Type Constraints

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

Examples