code: def predict(self):
          
          if self.w_ is not None:
              sigmoid = lambda t: 1. / (1. + np.exp(-t))
              return sigmoid(np.dot(self.centers, self.w_[:-1]) + self.w_[-1])
          else:
              # TODO the model is not trained
              pass
docs: Returns
          -------
          proba : ndarray, shape=(n_clusters, )
              The probability of given cluster being label 1.