public override void Init(IRepository repository, IEnumerable <string> releases)
{
base.Init(repository, releases);
double dd = repository.SelectionDSL()
.Commits().TillRevision(PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectDensity(PredictionRelease);
context.SetCommits(null, PredictionRelease);
regression = new LinearRegression();
foreach (var file in GetFilesInRevision(PredictionRelease))
{
double ddForFile = repository.SelectionDSL()
.Commits().TillRevision(PredictionRelease)
.Files().IdIs(file.ID)
.Modifications().InCommits().InFiles()
.CodeBlocks().InModifications().CalculateDefectDensity(PredictionRelease);
if (ddForFile >= dd)
{
context.SetFiles(e => e.IdIs(file.ID));
regression.AddTrainingData(
GetPredictorValuesFor(context)[0],
NumberOfFixedDefectsForFile(file.ID)
);
}
}
regression.Train();
}
private void TestLinearRegression()
{
LinearRegression linearRegression = new LinearRegression(trainingEpochs, learningRate);
linearRegression.Train(dataX, dataY);
(float[] results, float optimalWeights, float optimalBias) = linearRegression.Predict(testX);
//analytical solution coefficientVector=(X'*X)*X'*Y where X is the inputX with ones in the first column and Y is inputY: bias=0.7988 and weight=0.2516
Assert.Equal(0.309068531, optimalWeights, 6);
Assert.Equal(0.373608261, optimalBias, 6);
}
public override void Init(IRepository repository, IEnumerable<string> releases)
{
base.Init(repository, releases);
double dd = repository.SelectionDSL()
.Commits().TillRevision(PredictionRelease)
.Modifications().InCommits()
.CodeBlocks().InModifications().CalculateDefectDensity(PredictionRelease);
context.SetCommits(null, PredictionRelease);
regression = new LinearRegression();
foreach (var file in GetFilesInRevision(PredictionRelease))
{
double ddForFile = repository.SelectionDSL()
.Commits().TillRevision(PredictionRelease)
.Files().IdIs(file.ID)
.Modifications().InCommits().InFiles()
.CodeBlocks().InModifications().CalculateDefectDensity(PredictionRelease);
if (ddForFile >= dd)
{
context.SetFiles(e => e.IdIs(file.ID));
regression.AddTrainingData(
GetPredictorValuesFor(context)[0],
NumberOfFixedDefectsForFile(file.ID)
);
}
}
regression.Train();
}