simpeg.utils.GaussianMixtureWithPrior.fit#
- GaussianMixtureWithPrior.fit(X, y=None, debug=False)[source]#
Estimate model parameters with the EM algorithm.
[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 formax_iter
times until the change of likelihood or lower bound is less thantol
, otherwise, aConvergenceWarning
is raised. Ifwarm_start
isTrue
, thenn_init
is ignored and a single initialization is performed upon the first call. Upon consecutive calls, training starts where it left off.- Parameters:
- Xarray_like,
shape
(n_samples
,n_features
) 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
- Xarray_like,
- Returns:
- self
object
The fitted mixture.
- self