def predict(self, Xnew=None, filteronly=False, include_likelihood=True, balance=None, **kw):
if balance is None:<EOL><INDENT>p_balance = self.balance<EOL><DEDENT>else:<EOL><INDENT>p_balance = balance<EOL><DEDENT>(m, V) = self._raw_predict(Xnew,filteronly=filteronly, p_balance=p_balance)<EOL>if include_likelihood:<EOL><INDENT>V += float(self.likelihood.variance)<EOL><DEDENT>return m, V<EOL>
Inputs:
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balance: bool
Whether to balance or not the model as a whole