simpeg.utils.GaussianMixtureWithNonlinearRelationshipsWithPrior.fit_predict#
- GaussianMixtureWithNonlinearRelationshipsWithPrior.fit_predict(X, y=None, debug=False)[source]#
Estimate model parameters using X and predict the labels for X.
[modified from Scikit-Learn for Maximum A Posteriori estimates (MAP)] 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
ConvergenceWarningis raised. After fitting, it predicts the most probable label for the input data points.- Parameters:
- X(
n_samples,n_features) array_like List of n_features-dimensional data points. Each row corresponds to a single data point.
- y
Ignored Not used, present for API consistency by convention.
- debugbool, default:
False If
True, print debug statements
- X(
- Returns:
- (
n_samples)array Component labels.
- (