public override void Train(Split split)
{
UpdateFeatureBuilder(split);
Logger.Current.Info("Creating LibFm train and test files...");
// infer dataType and add negative samples in case of posFeedback data
IEnumerable <Feedback> negFeedback = Enumerable.Empty <Feedback>();
if (split.Container.DataReaders.Select(dr => dr.DataType).Contains(IO.DataType.PosFeedback))
{
this.DataType = IO.DataType.PosFeedback;
negFeedback = split.SampleNegativeFeedback((int)(split.Train.Count()));
}
var train = split.Train.Concat(negFeedback).Shuffle().Select(f => FeatureBuilder.GetLibFmFeatureVector(f));
var test = split.Test.Select(f => FeatureBuilder.GetLibFmFeatureVector(f));
string trainPath = "train.libfm";
string testPath = "test.libfm";
File.WriteAllLines(trainPath, train);
File.WriteAllLines(testPath, test);
string args = LibFmArguments.Union(new string[] { "-train", trainPath, "-test", testPath, "-out", _outputPath })
.Aggregate((a, b) => a + " " + b);
var libFm = new Process
{
StartInfo = new ProcessStartInfo
{
FileName = SetupParameters["libFmPath"],
Arguments = args,
UseShellExecute = false,
RedirectStandardOutput = true,
RedirectStandardError = true,
CreateNoWindow = true
}
};
libFm.OutputDataReceived += OnLibFmOutput;
Logger.Current.Info("Training and testing with LibFm...");
Logger.Current.Info("Running process:\n {0} {1}", SetupParameters["libFmPath"], libFm.StartInfo.Arguments);
PureTrainTime = (int)Wrap.MeasureTime(delegate()
{
libFm.Start();
libFm.BeginOutputReadLine();
libFm.WaitForExit();
}).TotalMilliseconds;
LoadFmModel();
_minTarget = split.Container.MinTarget;
_maxTarget = split.Container.MaxTarget;
}
public override void Train(Split split)
{
UpdateFeatureBuilder(split);
List <string> train = split.Train.Select(f => FeatureBuilder.GetLibFmFeatureVector(f)).ToList();
_libFm.CreateTrainSet(train, split.Container.MinTarget, split.Container.MaxTarget,
FeatureBuilder.GetNumMappedValues(), FeatureBuilder.Mapper.NumberOfEntities);
Logger.Current.Trace("Training with LibFm recommender...");
PureTrainTime = (int)Wrap.MeasureTime(delegate()
{
_libFm.Train();
}).TotalMilliseconds;
}
public override float Predict(Feedback feedback)
{
return(Predict(FeatureBuilder.GetLibFmFeatureVector(feedback)));
}
public override float Predict(string userId, string itemId)
{
return(Predict(FeatureBuilder.GetLibFmFeatureVector(userId, itemId)));
}
