docstr: [Initiate the prediction function]
  
  Args:
      Model
      input_data
      target_data
  
  Return:
      prediction column
      probabilities [if is_classifier]
docstr_tok: ["[","Initiate","the","prediction","function","]","Args",":","Model","input_data","target_data","Return",":","prediction","column","probabilities","[","if","is_classifier","]"]
code: def make_predictions(self):
      """[Initiate the prediction function]
  
      Args:
          Model
          input_data
          target_data
  
      Return:
          prediction column
          probabilities [if is_classifier]
  
      """
      if is_classification(self.model):
          if self.ct == None:
              prediction = self.model.predict(
                  self.input_data.to_numpy()
              )
              probabilities = self.model.predict_proba(
                  self.input_data.to_numpy()
              )
              return prediction, probabilities
          elif self.ct != None:
              prediction = self.model.predict(self.data_into_model())
              probabilities = self.model.predict_proba(
                  self.data_into_model()
              )
              return prediction, probabilities
          else:
              raise Exception(
                  (
                      "{} not supported. Please create an issue on Github"
                  ).format(self.model)
              )
  
      else:
          if self.ct == None:
              prediction = self.model.predict(self.input_data)
              return prediction
          elif self.ct != None:
              prediction = self.model.predict(self.data_into_model())
              return prediction
          else:
              raise Exception(
                  (
                      "{} not supported. Please create an issue on Github"
                  ).format(self.self.model)
              )
  
file_path: explainx/lib/models/modelprocessor.py
imports: from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
  import numpy
  import pandas
  from sklearn.preprocessing import LabelEncoder
  from typing import Dict, List, Union
  from sklearn.impute import SimpleImputer
  from explainx.lib.utils import is_classification
label_desc: Use image node_id 7 for calling the ModelProcessor obj's underlying member method code with example usage: obj.make_predictions() and returns: prediction,  probabilities, prediction, prediction,  probabilities, prediction