module `onnxrt.ops_cpu.op_svm_regressor`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_svm_regressor

Runtime operator.

Classes#

class	truncated documentation
`SVMRegressor`	SVMRegressor (ai.onnx.ml) ========================= Support Vector Machine regression prediction and one-class SVM anomaly …
`SVMRegressorCommon`
`SVMRegressorDouble`	SVMRegressorDouble (mlprodict) ============================== Version Onnx name: SVMRegressorDouble …
`SVMRegressorDoubleSchema`	Defines a schema for operators added in this package such as `SVMRegressorDouble`.

Properties#

property	truncated documentation
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default`	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_default_modified`	Returns the list of modified parameters.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_mandatory`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`args_optional`	Returns the list of optional arguments.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`__init__`
`_find_custom_operator_schema`	Finds a custom operator defined by this runtime.
`_find_custom_operator_schema`	Finds a custom operator defined by this runtime.
`_find_custom_operator_schema`	Finds a custom operator defined by this runtime.
`_get_typed_attributes`
`_get_typed_attributes`
`_get_typed_attributes`
`_init`
`_init`
`_init`
`_run`	This is a C++ implementation coming from onnxruntime. svm_regressor.cc. …
`_run`	This is a C++ implementation coming from onnxruntime. svm_regressor.cc. …
`_run`	This is a C++ implementation coming from onnxruntime. svm_regressor.cc. …

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_svm_regressor.SVMRegressor(ai.onnx.ml)#

Bases: SVMRegressorCommon

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

Attributes

coefficients: Support vector coefficients. default value cannot be automatically retrieved (FLOATS)
kernel_params: List of 3 elements containing gamma, coef0, and degree, in that order. Zero if unused for the kernel. default value cannot be automatically retrieved (FLOATS)
kernel_type: The kernel type, one of ‘LINEAR,’ ‘POLY,’ ‘RBF,’ ‘SIGMOID’. Default value is namekerneltypesLINEARtypeSTRING (STRING)
n_supports: The number of support vectors. Default value is namensupportsi0typeINT (INT)
one_class: Flag indicating whether the regression is a one-class SVM or not. Default value is nameoneclassi0typeINT (INT)
post_transform: Indicates the transform to apply to the score. One of ‘NONE,’ ‘SOFTMAX,’ ‘LOGISTIC,’ ‘SOFTMAX_ZERO,’ or ‘PROBIT.’ Default value is nameposttransformsNONEtypeSTRING (STRING)
rho: default value cannot be automatically retrieved (FLOATS)
support_vectors: Chosen support vectors default value cannot be automatically retrieved (FLOATS)

Inputs

X (heterogeneous)T: Data to be regressed.

Outputs

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

Type Constraints

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

Version

Onnx name: SVMRegressor

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

Runtime implementation: SVMRegressor

__init__(onnx_node, desc=None, **options)#

class mlprodict.onnxrt.ops_cpu.op_svm_regressor.SVMRegressorCommon(dtype, onnx_node, desc=None, expected_attributes=None, **options)#

Bases: OpRunUnaryNum

__init__(dtype, onnx_node, desc=None, expected_attributes=None, **options)#

_find_custom_operator_schema(op_name)#

Finds a custom operator defined by this runtime.

source on GitHub

_get_typed_attributes(k)#

_init(dtype)#

_run(x, attributes=None, verbose=0, fLOG=None)#

This is a C++ implementation coming from onnxruntime. svm_regressor.cc. See class RuntimeSVMRegressor.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_svm_regressor.SVMRegressorDouble(mlprodict)#

Bases: SVMRegressorCommon

Version

Onnx name: SVMRegressorDouble

This version of the operator has been available since version of domain mlprodict.

Runtime implementation: SVMRegressorDouble

__init__(onnx_node, desc=None, **options)#

class mlprodict.onnxrt.ops_cpu.op_svm_regressor.SVMRegressorDoubleSchema#

Bases: OperatorSchema

Defines a schema for operators added in this package such as SVMRegressorDouble.

source on GitHub

__init__()#

module onnxrt.ops_cpu.op_svm_regressor#

Short summary#

Classes#

Properties#

Methods#

Documentation#

module `onnxrt.ops_cpu.op_svm_regressor`#