code: def predict_proba(self, X):
          
          X_ = self._check_array(X)
          return sigmoid(dot(X_, self._coef))
docs: Probability estimates for samples in X.
  
          Parameters
          ----------
          X : array-like, shape = [n_samples, n_features]
  
          Returns
          -------
          T : array-like, shape = [n_samples, n_classes]
              The probability of the sample for each class in the model.