protected override Func <double, double> Distribution(IEnumerable <double> bugLifetimes)
{
ExponentialRegression expRegression = new ExponentialRegression();
foreach (var time in bugLifetimes)
{
expRegression.AddTrainingData(time, (double)bugLifetimes.Where(t => t <= time).Count() / bugLifetimes.Count());
}
expRegression.Train();
return(time =>
{
return expRegression.Predict(time);
});
}
/// <summary>
/// Initializing regression list
/// </summary>
/// <param name="xVals"></param>
/// <param name="yValsConv"></param>
/// <param name="file"></param>
/// <param name="predictDays"></param>
/// <param name="name"></param>
private void GetRegressionsList(double[] xVals, double[] yValsConv, CsvFile file, int predictDays, string name)
{
regressions.Clear();
PlotCanvas.Children.Clear();
AbstractRegression regression;
Brush brush = null;
if (ExponentialCheck.IsChecked == true)
{
regression = new ExponentialRegression(xVals, yValsConv);
brush = Brushes.Gold;
regressions.Add(new RegressionContainer(regression, predictDays, 0, file.Fields[0], name));
DrawPlot(regressions[regressions.Count - 1]);
}
if (LogarifmicCheck.IsChecked == true)
{
regression = new LogarifmicRegression(xVals, yValsConv);
brush = Brushes.Coral;
regressions.Add(new RegressionContainer(regression, predictDays, 1, file.Fields[0], name));
DrawPlot(regressions[regressions.Count - 1]);
}
if (HyperbolicCheck.IsChecked == true)
{
brush = Brushes.DeepPink;
regression = new HyperbolicRegression(xVals, yValsConv);
regressions.Add(new RegressionContainer(regression, predictDays, 2, file.Fields[0], name));
DrawPlot(regressions[regressions.Count - 1]);
}
if (SquareCheck.IsChecked == true)
{
brush = Brushes.ForestGreen;
regression = new SquareRegression(xVals, yValsConv);
regressions.Add(new RegressionContainer(regression, predictDays, 3, file.Fields[0], name));
DrawPlot(regressions[regressions.Count - 1]);
}
if (CubicCheck.IsChecked == true)
{
brush = Brushes.MidnightBlue;
regression = new CubicRegression(xVals, yValsConv);
regressions.Add(new RegressionContainer(regression, predictDays, 4, file.Fields[0], name));
DrawPlot(regressions[regressions.Count - 1]);
}
}
protected override Func<double, double> Distribution(IEnumerable<double> bugLifetimes)
{
ExponentialRegression expRegression = new ExponentialRegression();
foreach (var time in bugLifetimes)
{
expRegression.AddTrainingData(time, (double)bugLifetimes.Where(t => t <= time).Count() / bugLifetimes.Count());
}
expRegression.Train();
return time =>
{
return expRegression.Predict(time);
};
}
