mvpa2.clfs.meta.RegressionAsClassifierSensitivityAnalyzer¶
-
class
mvpa2.clfs.meta.
RegressionAsClassifierSensitivityAnalyzer
(*args_, **kwargs_)¶ Set sensitivity analyzer output to have proper labels
Notes
Available conditional attributes:
calling_time+
: Time (in seconds) it took to call the nodeclf_sensitivities
: Stores sensitivities of the proxied classifiernull_prob+
: Nonenull_t
: Noneraw_results
: Computed results before invoking postproc. Stored only if postproc is not None.trained_dataset
: The dataset it has been trained ontrained_nsamples+
: Number of samples it has been trained ontrained_targets+
: Set of unique targets (or any other space) it has been trained on (if present in the dataset trained on)training_time+
: Time (in seconds) it took to train the learner
(Conditional attributes enabled by default suffixed with
+
)Attributes
analyzer
auto_train
Whether the Learner performs automatic trainingwhen called untrained. clf
descr
Description of the object if any feature_ids
Return feature_ids used by the underlying classifier force_train
Whether the Learner enforces training upon every call. is_trained
null_dist
Return Null Distribution estimator pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results space
Processing space name of this node Methods
__call__
(ds)generate
(ds)Yield processing results. get_postproc
()Returns the post-processing node or None. get_space
()Query the processing space name of this node. reset
()set_postproc
(node)Assigns a post-processing node set_space
(name)Set the processing space name of this node. train
(ds)The default implementation calls _pretrain()
,_train()
, and finally_posttrain()
.untrain
()Reverts changes in the state of this node caused by previous training Initialize instance of ProxyClassifierSensitivityAnalyzer
Parameters: 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
Attributes
analyzer
auto_train
Whether the Learner performs automatic trainingwhen called untrained. clf
descr
Description of the object if any feature_ids
Return feature_ids used by the underlying classifier force_train
Whether the Learner enforces training upon every call. is_trained
null_dist
Return Null Distribution estimator pass_attr
Which attributes of the dataset or self.ca to pass into result dataset upon call postproc
Node to perform post-processing of results space
Processing space name of this node Methods
__call__
(ds)generate
(ds)Yield processing results. get_postproc
()Returns the post-processing node or None. get_space
()Query the processing space name of this node. reset
()set_postproc
(node)Assigns a post-processing node set_space
(name)Set the processing space name of this node. train
(ds)The default implementation calls _pretrain()
,_train()
, and finally_posttrain()
.untrain
()Reverts changes in the state of this node caused by previous training