Gaussian Naive Bayes Classifier

Basic implementation of Gaussian Naive Bayes classifier.

Inheritance diagram of mvpa2.clfs.gnb


accepts_dataset_as_samples(fx) Decorator to extract samples from Datasets.
dot(a, b[, out]) Dot product of two arrays.
ones(shape[, dtype, order]) Return a new array of given shape and type, filled with ones.
sum(a[, axis, dtype, out, keepdims]) Sum of array elements over a given axis.
zeros(shape[, dtype, order]) Return a new array of given shape and type, filled with zeros.


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
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
EnsureChoice(\*values) Ensure an input is element of a set of possible values
GNB(\*\*kwargs) Gaussian Naive Bayes Classifier.
GNBWeights(clf[, force_train]) SensitivityAnalyzer that reports the weights for a GNB classifier trained
Parameter(default[, constraints, ro, index, ...]) This class shall serve as a representation of a parameter.
Sensitivity(clf[, force_train]) Sensitivities of features for a given Classifier.