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Description
Describe the workflow you want to enable
Currently, there exists a lower_bound_ attribute in the fit_predict method of BaseMixture. However, the entire sequence of lower bounds is not accessible, which makes a convergence analysis more difficult to a user.
Describe your proposed solution
In addition to the lower_bound_ attribute, create a new attribute called lower_bounds_, which is a list of floats where each float is a lower bound set in
scikit-learn/sklearn/mixture/_base.py
Line 248 in 92c9b18
| lower_bound = self._compute_lower_bound(log_resp, log_prob_norm) |
Describe alternatives you've considered, if relevant
No response
Additional context
Creating the list and appending to it would increase memory costs (but not by much). Is this a possible concern?