Multivariate Pattern Analysis in Python

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# mvpa2.clfs.base

Base class for all XXX learners: classifiers and regressions.

Functions

`accepts_dataset_as_samples`(fx) | Decorator to extract samples from Datasets.
`accepts_samples_as_dataset`(fx) | Decorator to wrap samples into a Dataset.
`deepcopy`(x[, memo, _nil]) | Deep copy operation on arbitrary Python objects.
`idhash`(val) | Craft unique id+hash for an object
`is_datasetlike`(obj) | Check if an object looks like a Dataset.

Classes

`AttributeMap`([map, mapnumeric, ...]) | Map to translate literal values to numeric ones (and back).
`Classifier`([space]) | Abstract classifier class to be inherited by all classifiers ..
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`ConfusionMatrix`([labels, labels_map]) | Class to contain information and display confusion matrix.
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`Learner`([auto_train, force_train]) | Common trainable processing object.
`Measure`([null_dist]) | A measure computed from a `Dataset` All dataset measures support arbitrary transformation of the measure after it has been computed.
`Parameter`(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter.
`RegressionStatistics`(**kwargs) | Class to contain information and display on regression results.

Exceptions

`AttributeMap`([map, mapnumeric, ...]) | Map to translate literal values to numeric ones (and back).
`Classifier`([space]) | Abstract classifier class to be inherited by all classifiers ..
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`ConfusionMatrix`([labels, labels_map]) | Class to contain information and display confusion matrix.
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`Learner`([auto_train, force_train]) | Common trainable processing object.
`Measure`([null_dist]) | A measure computed from a `Dataset` All dataset measures support arbitrary transformation of the measure after it has been computed.
`Parameter`(default[, ro, index, value, name, doc]) | This class shall serve as a representation of a parameter.
`RegressionStatistics`(**kwargs) | Class to contain information and display on regression results.

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