def predict_quantiles(self, Xnew=None, quantiles=(<NUM_LIT>, <NUM_LIT>), balance=None, **kw):
if balance is None:<EOL><INDENT>p_balance = self.balance<EOL><DEDENT>else:<EOL><INDENT>p_balance = balance<EOL><DEDENT>mu, var = self._raw_predict(Xnew, p_balance=p_balance)<EOL>return  [stats.norm.ppf(q/<NUM_LIT>)*np.sqrt(var + float(self.Gaussian_noise.variance)) + mu for q in quantiles]<EOL>
Inputs:
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balance: bool
Whether to balance or not the model as a whole