public RegressionResult PerformRegression(MergedBacteria bacteria)
{
var trainSize = (int)(bacteria.Bacterium1.Measurements.Count() / 100.0 * TrainSizePercentage);
var trainX = bacteria.Bacterium1.Measurements.Take(trainSize).ToArray();
var testX = bacteria.Bacterium1.Measurements.Skip(trainSize).ToArray();
var trainY = bacteria.Bacterium2.Measurements.Take(trainSize).ToArray();
var testY = bacteria.Bacterium2.Measurements.Skip(trainSize).ToArray();
var result = RegressionModel.PerformRegression(trainX, trainY, testX, testY);
result.TrainX = trainX;
result.TrainY = trainY;
result.TestX = testX;
result.TestY = testY;
result.Error = new SquareLoss(trainX).Loss(result.PredictionOnTrainingSet);
return(result);
}
public static MergedBacteria MergeBacteria(Bacterium b1, Bacterium b2)
{
var merged = new MergedBacteria()
{
Bacterium1 = b1,
Bacterium2 = b2
};
merged.Points = new List <Tuple <double, double> >();
for (var i = 0; i < b1.Measurements.Count; i++)
{
merged.Points.Add(new Tuple <double, double>(b1.Measurements[i], b2.Measurements[i]));
}
merged.CosineDistance = 1 - Distance.Cosine(b1.Measurements.ToArray(), b2.Measurements.ToArray());
merged.SpearmanCorrelation = Correlation.Spearman(b1.Measurements, b2.Measurements);
merged.PearsonCorrelation = Correlation.Pearson(b1.Measurements, b2.Measurements);
return(merged);
}
