Package mvpa :: Package clfs :: Module gpr :: Class GPRLinearWeights

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# Class GPRLinearWeights

source code

`SensitivityAnalyzer` that reports the weights GPR trained on a given Dataset.

In case of KernelLinear compute explicitly the coefficients of the linear regression, together with their variances (if requested).

Note that the intercept is not computed.

Nested Classes | [hide private]

Inherited from `misc.state.ClassWithCollections`: `__metaclass__`

Instance Methods | [hide private]

_call(self, dataset) Extract weights from GPR | source code

Inherited from `measures.base.Sensitivity`: `__call__`, `__init__`, `__repr__`, `feature_ids`, `untrain`

Inherited from `measures.base.Sensitivity` (private): `_setClassifier`

Inherited from `measures.base.FeaturewiseDatasetMeasure`: `combiner`

Inherited from `measures.base.FeaturewiseDatasetMeasure` (private): `_postcall`

Inherited from `measures.base.DatasetMeasure`: `null_dist`, `transformer`

Inherited from `misc.state.ClassWithCollections`: `__getattribute__`, `__new__`, `__setattr__`, `__str__`, `reset`

Inherited from `object`: `__delattr__`, `__format__`, `__hash__`, `__reduce__`, `__reduce_ex__`, `__sizeof__`, `__subclasshook__`

Class Variables | [hide private]

| variances = `StateVariable(enabled= False, doc= "Variances of t`...``
| _LEGAL_CLFS = `[GPR]` If Sensitivity is classifier specific, classes of classifiers should be listed in the list
Inherited from `measures.base.Sensitivity`: `clf` Inherited from `measures.base.FeaturewiseDatasetMeasure`: `base_sensitivities` Inherited from `measures.base.DatasetMeasure`: `__doc__`, `null_prob`, `null_t`, `raw_results` Inherited from `misc.state.ClassWithCollections`: `_DEV__doc__`, `descr`

Instance Variables | [hide private]

Inherited from `measures.base.Sensitivity` (private): `_force_training`

Properties | [hide private]

Inherited from `object`: `__class__`

Method Details | [hide private]

### _call(self, dataset)

source code

Extract weights from GPR

Overrides: measures.base.DatasetMeasure._call

Class Variable Details | [hide private]

### variances

Value:

      StateVariable(enabled= False, doc= "Variances of the weights (for Kern
      elLinear)")