code: def __fit_predict(self, freq: np.array, metric: np.array) -> np.array:
      regressor = self.regressor.fit(freq.reshape(-1, 1), metric)
      pred = regressor.predict(freq.reshape(-1, 1))
      freq_est_metric = pred.T[0]
      return freq_est_metric
  
imports: from typing import Optional, Callable, List
  import numpy
  import pandas
  from scattertext.termranking import AbsoluteFrequencyRanker
  from scipy.sparse import csc_matrix, csr_matrix
  from sklearn.preprocessing import StandardScaler
  from scattertext.smoothing.lowess import Lowess
  from scattertext.termranking.TermRanker import TermRanker
  from scattertext.TermDocMatrix import TermDocMatrix
label_desc: Use image node_id 16 for calling the Dispersion obj's underlying member method code with example usage: obj.__fit_predict(freq, metric) and returns: freq_est_metric