def get_params(self, deep=True):
"""Overrides superclass get_params() to allow superclass hyperparameters
to be returned as well.
This allows for tuning any parameters from the parent KMeans class
without having to list each parameter in the KMeansMM __init__() function.
Taken from https://stackoverflow.com/questions/51430484/how-to-subclass-a-vectorizer-in-scikit-learn-without-repeating-all-parameters-in.
Parameters
----------
deep : boolean, optional
If True, will return the parameters for this estimator and
contained subobjects that are estimators.
Returns
-------
params : mapping of string to any
Parameter names mapped to their values.
"""
params = super().get_params(deep)
cp = copy.copy(self)
cp.__class__ = KMeans
params.update(KMeans.get_params(cp, deep))
return params
