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