LR¶
- Reference:
Matthew Richardson et al. “Predicting Clicks Estimating the Click-Through Rate for New Ads.” in WWW 2007.
- class recbole.model.context_aware_recommender.lr.LR(config, dataset)[source]¶
Bases:
recbole.model.abstract_recommender.ContextRecommenderLR 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:
\[ \begin{align}\begin{aligned}CTR = \frac{1}{1+e^{-Z}}\\Z = \sum_{i} {w_i}{x_i}\end{aligned}\end{align} \]- calculate_loss(interaction)[source]¶
Calculate the training loss for a batch data.
- Parameters
interaction (Interaction) – Interaction class of the batch.
- Returns
Training loss, shape: []
- Return type
torch.Tensor
- forward(interaction)[source]¶
Defines the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Moduleinstance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.
- predict(interaction)[source]¶
Predict the scores between users and items.
- Parameters
interaction (Interaction) – Interaction class of the batch.
- Returns
Predicted scores for given users and items, shape: [batch_size]
- Return type
torch.Tensor
- training: bool¶