mvpa2.clfs.meta.ProxyClassifier

Inheritance diagram of ProxyClassifier

class mvpa2.clfs.meta.ProxyClassifier(clf, **kwargs)

Classifier which decorates another classifier

Possible uses:

  • modify data somehow prior training/testing: * normalization * feature selection * modification
  • optimized classifier?

Notes

Available conditional attributes:

  • calling_time+: Time (in seconds) it took to call the node
  • estimates+: Internal classifier estimates the most recent predictions are based on
  • predicting_time+: Time (in seconds) which took classifier to predict
  • predictions+: Most recent set of predictions
  • raw_results: Computed results before invoking postproc. Stored only if postproc is not None.
  • trained_dataset: The dataset it has been trained on
  • trained_nsamples+: Number of samples it has been trained on
  • trained_targets+: Set of unique targets it has been trained on
  • training_stats: Confusion matrix of learning performance
  • training_time+: Time (in seconds) it took to train the learner

(Conditional attributes enabled by default suffixed with +)

Initialize the instance of ProxyClassifier

Parameters :

clf : Classifier

Classifier to proxy, i.e. to use after decoration

enable_ca : None or list of str

Names of the conditional attributes which should be enabled in addition to the default ones

disable_ca : None or list of str

Names of the conditional attributes which should be disabled

auto_train : bool

Flag whether the learner will automatically train itself on the input dataset when called untrained.

force_train : bool

Flag whether the learner will enforce training on the input dataset upon every call.

space: str, optional :

Name of the ‘processing space’. The actual meaning of this argument heavily depends on the sub-class implementation. In general, this is a trigger that tells the node to compute and store information about the input data that is “interesting” in the context of the corresponding processing in the output dataset.

postproc : Node instance, optional

Node to perform post-processing of results. This node is applied in __call__() to perform a final processing step on the to be result dataset. If None, nothing is done.

descr : str

Description of the instance

clf

Used Classifier

get_sensitivity_analyzer(*args_, **kwargs_)
summary()

NeuroDebian

NITRC-listed