private static void TrainForItemPrediction(Mapping userMapping, Mapping itemMapping, String[] args)
{
var training_data = ItemData.Read(trainingCompactFileForItems, userMapping, itemMapping);
itemRecommender = new CustomBPRMF();
if (File.Exists(Path.Combine(args[2], "model")))
{
Console.WriteLine("Skipping training, Loading saved model");
itemRecommender.LoadModel(Path.Combine(args[2], "model"));
itemRecommender.Feedback = training_data;
return;
}
Console.WriteLine("Training model for Item Prediction, this may take a while...");
itemRecommender.Feedback = training_data;
itemRecommender.NumFactors = 50;
itemRecommender.NumIter = 100;
itemRecommender.Train();
itemRecommender.SaveModel(Path.Combine(args[2], "model"));
}
private static void TrainForItemPrediction(Mapping userMapping, Mapping itemMapping, String[] args)
{
var training_data = ItemData.Read(trainingCompactFileForItems, userMapping, itemMapping);
itemRecommender = new CustomBPRMF();
if (File.Exists(Path.Combine(args[2], "model")))
{
Console.WriteLine("Skipping training, Loading saved model");
itemRecommender.LoadModel(Path.Combine(args[2], "model"));
itemRecommender.Feedback = training_data;
return;
}
Console.WriteLine("Training model for Item Prediction, this may take a while...");
itemRecommender.Feedback = training_data;
itemRecommender.NumFactors = 50;
itemRecommender.NumIter = 100;
itemRecommender.Train();
itemRecommender.SaveModel(Path.Combine(args[2], "model"));
}