public ProcessResult GetProcessResult(PipelineContext context)
{
var pr = new ProcessResult();
pr["MediaLite_RMSE"] = context.GetAsString("MediaLite_RMSE");
pr["MediaLite_MAE"] = context.GetAsString("MediaLite_MAE");
return(pr);
}
public ProcessResult GetProcessResult(PipelineContext context)
{
var pr = new ProcessResult();
pr["LibFmTrainRMSE"] = context.GetAsString("LibFmTrainRMSE");
pr["LibFmTestRMSE"] = context.GetAsString("LibFmTestRMSE");
pr["LibFmTestMAE"] = context.GetAsString("LibFmTestMAE");
return(pr);
}
public ProcessConfiguration GetConfiguration(PipelineContext context)
{
var pc = new ProcessConfiguration();
pc["Recommender"] = _recommender.GetType().Name;
pc["TrainFile"] = context.GetAsString("TrainFile");
pc["TestFile"] = context.GetAsString("TestFile");
return(pc);
}
public ProcessResult GetProcessResult(PipelineContext context)
{
var pr = new ProcessResult();
pr["TrainFile"] = context.GetAsString("TrainFile");
pr["TestFile"] = context.GetAsString("TestFile");
pr["TargetDomainTrainCount"] = context.GetAsString("TargetDomainTrainCount");
pr["TargetDomainTest"] = context.GetAsString("TargetDomainTest");
pr["AuxDomainsCount"] = context.GetAsString("AuxDomainsCount");
return(pr);
}
public ProcessConfiguration GetConfiguration(PipelineContext context)
{
var pc = new ProcessConfiguration();
pc["LearningAlgorithm"] = LearningAlgorithm.ToString();
pc["Iterations"] = Iterations.ToString();
pc["Dimensions"] = Dimensions;
pc["LearningRate"] = LearningRate.ToString();
pc["TrainFile"] = context.GetAsString("TrainFile");
pc["TestFile"] = context.GetAsString("TestFile");
pc["AdditionalArgs"] = _additionalArgs;
return(pc);
}
public ProcessResult GetProcessResult(PipelineContext context)
{
var pr = new ProcessResult();
pr["MovieLensFile"] = context.GetAsString("MovieLensFile");
return(pr);
}
public void Process(PipelineContext context)
{
var products = context["AmazonProducts"] as IList <AmazonProduct>;
string amazonDataFile = context.GetAsString("AmazonDataFile");
var outputFile = string.Format("{0}\\{1}4.libfm", amazonDataFile.GetDirectoryPath(), amazonDataFile.GetFileName());
var featDic = new Dictionary <string, int>();
ConvertToLibFmFile(products, outputFile, featDic);
context["LibFmFile"] = outputFile;
}
public override void Process(PipelineContext context)
{
string movieLensTrain = context.GetAsString("TrainFile");
string movieLensTest = context.GetAsString("TestFile");
string libFmTrain = movieLensTrain.GetDirectoryPath() + "\\" + movieLensTrain.GetFileName() + ".libfm";
string libFmTest = movieLensTest.GetDirectoryPath() + "\\" + movieLensTest.GetFileName() + ".libfm";
if (!File.Exists(libFmTrain) || !UseCach)
{
var featDic = new Dictionary <string, int>();
ConvertToLibFmFile(movieLensTrain, libFmTrain, featDic);
ConvertToLibFmFile(movieLensTest, libFmTest, featDic);
}
else
{
Console.WriteLine("==> loading cached data");
}
context["TrainFile"] = libFmTrain;
context["TestFile"] = libFmTest;
}
public void Process(PipelineContext context)
{
string movieLensTrain = context.GetAsString("TrainFile");
string movieLensTest = context.GetAsString("TestFile");
var usersMap = new Mapping();
var itemsMap = new Mapping();
IRatings trainSet = ReadData(movieLensTrain, usersMap, itemsMap);
IRatings testSet = ReadData(movieLensTest, usersMap, itemsMap);
var recom = _recommender as IRatingPredictor;
recom.Ratings = trainSet;
Console.WriteLine("Training...");
recom.Train();
Console.WriteLine("Testing...");
var results = recom.Evaluate(testSet);
context["MediaLite_RMSE"] = results["RMSE"];
context["MediaLite_MAE"] = results["MAE"];
}
public override void Process(PipelineContext context)
{
string movieLensFile = context.GetAsString("MovieLensFile");
var ratings = File.ReadAllLines(movieLensFile).Select(l => new ItemRating(l))
.GroupBy(r => r.UserId)
.Where(g => g.Count() >= _minNumRatings)
.SelectMany(g => g.Select(r => r.ToString()));
string outputFile = string.Format("{0}\\{1}-filter{2}.ml",
movieLensFile.GetDirectoryPath(), movieLensFile.GetFileName(), _minNumRatings);
File.WriteAllLines(outputFile, ratings.Shuffle());
context["MovieLensFile"] = outputFile;
}
public override void Process(PipelineContext context)
{
string inputFile = context.GetAsString(ContextName);
string trainFile = String.Format("{0}\\{1}-train{2}.{3}",
inputFile.GetDirectoryPath(), inputFile.GetFileName(), TrainRatio.ToString(), inputFile.GetFileExtension());
string testFile = String.Format("{0}\\{1}-test{2}.{3}",
inputFile.GetDirectoryPath(), inputFile.GetFileName(), TrainRatio.ToString(), inputFile.GetFileExtension());
if (!File.Exists(trainFile) || !UseCach)
{
Spilit(inputFile, trainFile, testFile, TrainRatio);
}
else
{
Console.WriteLine("==> loading cached data");
}
context["TrainFile"] = trainFile;
context["TestFile"] = testFile;
}
public void Process(PipelineContext context)
{
string libFmTrain = context.GetAsString("TrainFile");
string libFmTest = context.GetAsString("TestFile");
_testOutput = string.Format("{0}\\{1}.out", libFmTest.GetDirectoryPath(), libFmTest.GetFileName());
var libFm = new Process
{
StartInfo = new ProcessStartInfo
{
FileName = _libFmPath,
Arguments = BuildArguments(libFmTrain, libFmTest),
UseShellExecute = false,
RedirectStandardOutput = true,
RedirectStandardError = true,
CreateNoWindow = true
}
};
string libFMTrainRMSE = "", libFMTestRMSE = "";
double prevRMSE = double.MaxValue;
int iter = 0;
libFm.OutputDataReceived += (p, dataLine) =>
{
var data = dataLine.Data;
if (data != null && (data.StartsWith("Loading") || data.StartsWith("#")))
{
Console.WriteLine(dataLine.Data);
// Store the results of this apprach in pipeline context
if (data.StartsWith("#Iter"))
{
libFMTrainRMSE = data.Substring(data.IndexOf("Train") + 6, 6);
libFMTestRMSE = data.Substring(data.IndexOf("Test") + 5);
// Stop libFm if there was no improvement in RMSE
// Note: stopping LibFm will prevent the output file to be created
if (StopWhenNoImprovment)
{
double current = double.Parse(libFMTestRMSE);
if (current > prevRMSE)
{
libFm.Kill();
}
else
{
prevRMSE = current;
}
}
iter++;
}
}
};
libFm.Start();
libFm.BeginOutputReadLine();
libFm.WaitForExit();
context["LibFmTrainRMSE"] = libFMTrainRMSE;
context["LibFmTestRMSE"] = libFMTestRMSE;
// If this file exists it means the process finished normally and the MAE can be calculated
if (File.Exists(_testOutput))
{
context["LibFmTestMAE"] = CalculateMAE(libFmTest);
}
else
{
context["LibFmTestMAE"] = "LibFM exited at iter " + iter;
}
}