class_docstr: bla
docstr: bla
code: def get_exp_from_hoeffding(self, image, hoeffding_exp):
      """
      bla
      """
      ret = []
  
      features = hoeffding_exp["feature"]
      means = hoeffding_exp["mean"]
      if "negatives" not in hoeffding_exp:
          negatives_ = [np.array([]) for x in features]
      else:
          negatives_ = hoeffding_exp["negatives"]
      for f, mean, negatives in zip(features, means, negatives_):
          train_support = 0
          name = ""
          if negatives.shape[0] > 0:
              unique_negatives = np.vstack(
                  {tuple(row) for row in negatives}
              )
              distances = sklearn.metrics.pairwise_distances(
                  np.ones((1, negatives.shape[1])), unique_negatives
              )
              negative_arrays = unique_negatives[
                  np.argsort(distances)[0][:4]
              ]
              negatives = []
              for n in negative_arrays:
                  negatives.append(n)
          else:
              negatives = []
          ret.append((f, name, mean, negatives, train_support))
      return ret
  
file_path: anchor/anchor/anchor_image.py
imports: from .None import anchor_base
  import numpy
  import sklearn
label_desc: Use image node_id 4 for calling the AnchorImage obj's underlying member method code with example usage: obj.get_exp_from_hoeffding(image, hoeffding_exp) and returns: ret