mvpa2.clfs.gnbΒΆ
Gaussian Naive Bayes Classifier
Basic implementation of Gaussian Naive Bayes classifier.
Functions
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. |
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 |
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. |
