class_docstr: LR is a context-based recommendation model.
  It aims to predict the CTR given a set of features by using logistic regression,
  which is ideally suited for probabilities as it always predicts a value between 0 and 1:
  
  .. math::
      CTR = \frac{1}{1+e^{-Z}}
  
      Z = \sum_{i} {w_i}{x_i}
code: def __init__(self, config, dataset):
      super(LR, self).__init__(config, dataset)
  
      self.sigmoid = nn.Sigmoid()
      self.loss = nn.BCEWithLogitsLoss()
  
      # parameters initialization
      self.apply(self._init_weights)
  
file_path: RecBole/recbole/model/context_aware_recommender/lr.py
imports: import torch.nn
  from torch.nn.init import xavier_normal_
  from recbole.model.abstract_recommender import ContextRecommender
label_desc: Use image node_id 1 to create a new LR object from inherited base classes: ContextRecommender with example: obj = LR(config, dataset)