code: def predict(self, X):
      pred = self.decision_function(X)
      out = self.label_binarizer_.inverse_transform(pred)
  
      if hasattr(self, "label_encoder_"):
          out = self.label_encoder_.inverse_transform(out)
  
      return out
  
imports: import numpy
  import scipy.sparse
  import scipy.special
  from sklearn.base import BaseEstimator
  from sklearn.base import ClassifierMixin, RegressorMixin
  from sklearn.utils.extmath import safe_sparse_dot
  from sklearn.preprocessing import LabelBinarizer
  from sklearn.preprocessing import LabelEncoder
  from .randomkit import RandomState
label_desc: Use image node_id 5 for calling the BaseClassifier obj's underlying member method code with example usage: obj.predict(X) and returns: out