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 forward(self, interaction):
      output = self.first_order_linear(interaction)
      return output.squeeze(-1)
  
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 3 for calling the LR obj's underlying member method code with example usage: obj.forward(interaction) and returns: output