code: def b_fit_score(self, x, y):
          
          x = np.reshape(minmax_scale(x), (-1, 1))
          y = np.reshape(minmax_scale(y), (-1, 1))
          poly = PolynomialFeatures(degree=self.degree)
          poly_x = poly.fit_transform(x)
  
          poly_x[:,1] = 0
          poly_x[:,2] = 0
  
          regressor = LinearRegression()
          regressor.fit(poly_x, y)
  
          y_predict = regressor.predict(poly_x)
          error = mean_squared_error(y_predict, y)
  
          return error
docs: Compute the RECI fit score
  
          Args:
              x (numpy.ndarray): Variable 1
              y (numpy.ndarray): Variable 2
  
          Returns:
              float: RECI fit score