multidim.models.GaussianMixtureClassifier

class multidim.models.GaussianMixtureClassifier(stop_level=None, **kwargs)

A scikit-learn classification estimator, for any sort of Gaussian mixture model.

A Gaussian mixture module is a collection of labelled Gaussian functions

This is provided mainly to provide a parent class for CDER.

GaussianMixtureClassifier.evaluate(x)	Evaluate all gaussians against a pointcloud
GaussianMixtureClassifier.fit(*training)	Fit this estimator to training data.
GaussianMixtureClassifier.gausscoords()	This is the method to overwrite for specific models!
GaussianMixtureClassifier.get_params([deep])	Pass original kwargs internally.
GaussianMixtureClassifier.plot(canvas[, style])	Plot a CDER model, using matplotlib or bokeh
GaussianMixtureClassifier.predict(pointclouds)	Predict labels of given pointclouds, based on previous training data fed to fit().
GaussianMixtureClassifier.runit(pointclouds)
GaussianMixtureClassifier.score(pointclouds, …)	Score predicted labels against known labels.
GaussianMixtureClassifier.set_params(**params)	Set the parameters of this estimator.