ai.onnx.ml - LinearRegressor#

LinearRegressor - 1#

Version

  • name: LinearRegressor (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 : Weights of the model(s).

  • intercepts - FLOATS : Weights of the intercepts, if used.

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

  • targets - INT : The total number of regression targets, 1 if not defined.

Inputs

  • X (heterogeneous) - T:

Outputs

  • Y (heterogeneous) - tensor(float):

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(int32), tensor(int64) ): The input must be a tensor of a numeric type.

Examples