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11.12.1. astroML.classification.GMMBayes

class astroML.classification.GMMBayes(n_components=1, **kwargs)

GMM Bayes Classifier

This is a generalization to the Naive Bayes classifier: rather than modeling the distribution of each class with axis-aligned gaussians, GMMBayes models the distribution of each class with mixtures of gaussians. This can lead to better classification in some cases.

Parameters :

n_components : int or list

number of components to use in the gmm. If specified as a list, it must match the number of class labels

other keywords are passed directly to GMM :

Methods

fit(X, y)
get_params([deep]) Get parameters for this estimator.
predict(X) Perform classification on an array of test vectors X.
predict_log_proba(X) Return log-probability estimates for the test vector X.
predict_proba(X) Return probability estimates for the test vector X.
score(X, y) Returns the mean accuracy on the given test data and labels.
set_params(**params) Set the parameters of this estimator.
__init__(n_components=1, **kwargs)