class_docstr: Base Evaluation Method
  
  Parameters
  ----------
  data: array-like, required
      Raw preference data in the triplet format [(user_id, item_id, rating_value)].
  
  fmt: str, default: 'UIR'
      Format of the input data. Currently, we are supporting:
  
      'UIR': User, Item, Rating
      'UIRT': User, Item, Rating, Timestamp
  
  rating_threshold: float, optional, default: 1.0
      Threshold used to binarize rating values into positive or negative feedback for
      model evaluation using ranking metrics (rating metrics are not affected).
  
  seed: int, optional, default: None
      Random seed for reproducibility.
  
  exclude_unknowns: bool, optional, default: True
      If `True`, unknown users and items will be ignored during model evaluation.
  
  verbose: bool, optional, default: False
      Output running log.
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code: def user_image(self):
      return self.__user_image
  
imports: from collections import OrderedDict
  import time
  import numpy
  from scipy.sparse import csr_matrix
  from tqdm.auto import tqdm
  from ..data import FeatureModality
  from ..data import TextModality, ReviewModality
  from ..data import ImageModality
  from ..data import GraphModality
  from ..data import SentimentModality
  from ..data import Dataset
  from ..metrics import RatingMetric
  from ..metrics import RankingMetric
  from ..experiment.result import Result
  from ..utils import get_rng
label_desc: Use image node_id 8 for calling the BaseMethod obj's underlying member method code with example usage: obj.user_image() and returns: self