docstr: Parameters
  ----------
  alpha_w : np.float
          The constant prior.
docstr_tok: ["Parameters","--","--","--","--","--","alpha_w",":","np.float","The","constant","prior","."]
code: def __init__(self, alpha_w=1, ranker=AbsoluteFrequencyRanker):
      """
      Parameters
      ----------
      alpha_w : np.float
              The constant prior.
      """
      self.alpha_w = alpha_w
  
file_path: scattertext/scattertext/termsignificance/LogOddsRatioSmoothed.py
imports: import numpy
  from scipy.special import ndtr
  from scattertext.Scalers import scale_neg_1_to_1_with_zero_mean_abs_max
  from scattertext.termranking import AbsoluteFrequencyRanker
  from scattertext.termsignificance.TermSignificance import TermSignificance
label_desc: Use image node_id 1 to create a new LogOddsRatioSmoothed object from inherited base classes: TermSignificance with example: obj = LogOddsRatioSmoothed(alpha_w, ranker)