class_docstr: Class random hyperplane classifier, used in experiments.
docstr: Predict labels on data set X.
code: def predict(self, X):
      """Predict labels on data set X."""
      beta = self.coefficient
      n = X.shape[0]
      y = []
      for i in range(n):
          x_i = X.iloc[i, :]
          c_1 = np.dot(beta, x_i)
          y_i = int(c_1 < 0)
          y.append(y_i)
      return y
  
file_path: AIF360/aif360/algorithms/inprocessing/gerryfair/reg_oracle_class.py
imports: import numpy
label_desc: Use image node_id 2 for calling the RandomLinearThresh obj's underlying member method code with example usage: obj.predict(X) and returns: y