docstr: Parameters
  ----------
  scaler_algo : str
          Function that scales an array to a range \in [0 and 1]. Use 'percentile', 'normcdf'. Default normcdf.
  beta : float
          Beta in (1+B^2) * (Scale(P(w|c)) * Scale(P(c|w)))/(B^2*Scale(P(w|c)) + Scale(P(c|w))). Defaults to 1.
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code: def __init__(
      self, scaler_algo=DEFAULT_SCALER_ALGO, beta=DEFAULT_BETA
  ):
      """
      Parameters
      ----------
      scaler_algo : str
              Function that scales an array to a range \in [0 and 1]. Use 'percentile', 'normcdf'. Default normcdf.
      beta : float
              Beta in (1+B^2) * (Scale(P(w|c)) * Scale(P(c|w)))/(B^2*Scale(P(w|c)) + Scale(P(c|w))). Defaults to 1.
      """
      self.scaler_algo = scaler_algo
      self.beta = beta
  
file_path: scattertext/scattertext/termsignificance/ScaledFScoreSignificance.py
imports: import numpy
  from scattertext.termscoring.ScaledFScore import ScaledFZScore
  from scattertext.Common import DEFAULT_SCALER_ALGO, DEFAULT_BETA
  from scattertext.termscoring import ScaledFScore
  from scipy.stats import norm
  from scattertext.termsignificance.TermSignificance import TermSignificance
label_desc: Use image node_id 1 to create a new ScaledFScoreSignificance object from inherited base classes: TermSignificance with example: obj = ScaledFScoreSignificance(scaler_algo, beta)