Learners : Matchbox recommender : Command-line runners

Trainer

Training is performed using the Train argument to Learner Recommender. It takes as input a training dataset and outputs a serialized trained model, which can be loaded later for making predictions. Training takes in a number of arguments, explained in the Setting up a recommender section. There is more detail on the training procedure in the Training section.

Required parameters

  • training-data - training dataset
  • trained-model - trained model file

Optional parameters

  • traits - number of traits (defaults to 4)
  • iterations - number of inference iterations (defaults to 20)
  • batches - number of batches to split the training data into (defaults to 1)
  • use-user-features - use user features in the model (defaults to False)
  • use-item-features - use item features in the model (defaults to False)

Example

Learner Recommender Train --training-data TrainingSet.dat
                          --trained-model TrainedMatchbox.bin 
                          --traits 5
                          --iterations 30
                          --batches 4
                          --use-user-features 
                          --use-item-features

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