simpeg.utils.WeightedGaussianMixture.fit_predict

WeightedGaussianMixture.fit_predict(X, y=None)

Estimate model parameters using X and predict the labels for X.

The method fits the model n_init times and sets the parameters with which the model has the largest likelihood or lower bound. Within each trial, the method iterates between E-step and M-step for max_iter times until the change of likelihood or lower bound is less than tol, otherwise, a ConvergenceWarning is raised. After fitting, it predicts the most probable label for the input data points.

Added in version 0.20.

Parameters:

Xarray_like of shape (n_samples, n_features)

List of n_features-dimensional data points. Each row corresponds to a single data point.

yIgnored

Not used, present for API consistency by convention.

Returns:

labelsarray, shape (n_samples,)

Component labels.