class_docstr: Igel is the base model to use the fit, evaluate and predict functions of the sklearn library
class_docstr_tok: ["Igel","is","the","base","model","to","use","the","fit",",","evaluate","and","predict","functions","of","the","sklearn","library"]
docstr: preprocess predict data to get similar data to the one used when training the model
docstr_tok: ["preprocess","predict","data","to","get","similar","data","to","the","one","used","when","training","the","model"]
code: def _prepare_predict_data(self):
      """
      preprocess predict data to get similar data to the one used when training the model
      """
      return self._process_data(target="predict")
  
imports: import json
  import logging
  import os
  import warnings
  import joblib
  import numpy
  import pandas
  from sklearn.model_selection import cross_validate, train_test_split
  from sklearn.multioutput import MultiOutputClassifier, MultiOutputRegressor
  from skl2onnx import convert_sklearn
  from skl2onnx.common.data_types import FloatTensorType
label_desc: Use image node_id 9 for calling the Igel obj's underlying member method code with example usage: obj._prepare_predict_data() and returns: self