public static double MFactorCarbonPlus(List<MFCPData> matrixStateData, MFCPData currentStateData)
{
const int nFeatures = 4;
int nFeaturesCoefficcients;
int info = 0;
var inVector = new double[matrixStateData.Count, nFeatures + 1];
double[] coefficcients;
var lm = new alglib.linearmodel();
var lr = new alglib.lrreport();
int lenghtData = matrixStateData.Count;
for (int item = 0; item < lenghtData; item++)
{
inVector[item, 0] = matrixStateData[item].TimeFromX; // X1
inVector[item, 1] = matrixStateData[item].CarbonOxideIVP; // X2
inVector[item, 2] = matrixStateData[item].CarbonMonoxideVP; // X3
inVector[item, 3] = matrixStateData[item].CarbonOxideVP; // X4
inVector[item, 4] = matrixStateData[item].SteelCarbonPercent; // Y
}
alglib.lrbuild(inVector, lenghtData, nFeatures, out info, out lm, out lr);
if (info != 1)
{
return info;
}
alglib.lrunpack(lm, out coefficcients, out nFeaturesCoefficcients);
if (nFeaturesCoefficcients != nFeatures)
{
return -2.011;
}
double calculatedCarbon = coefficcients[4];
calculatedCarbon += coefficcients[0] * currentStateData.TimeFromX;
calculatedCarbon += coefficcients[1] * currentStateData.CarbonOxideIVP;
calculatedCarbon += coefficcients[2] * currentStateData.CarbonMonoxideVP;
calculatedCarbon += coefficcients[3] * currentStateData.CarbonOxideVP;
return calculatedCarbon;
}
private static IRegressionEnsembleSolution CreateEnsembleSolution(List<IRegressionModel> models,
IRegressionProblemData problemData) {
var rows = problemData.TrainingPartition.Size;
var features = models.Count;
double[,] inputMatrix = new double[rows, features + 1];
//add model estimates
for (int m = 0; m < models.Count; m++) {
var model = models[m];
var estimates = model.GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices);
int estimatesCounter = 0;
foreach (var estimate in estimates) {
inputMatrix[estimatesCounter, m] = estimate;
estimatesCounter++;
}
}
//add target
var targets = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices);
int targetCounter = 0;
foreach (var target in targets) {
inputMatrix[targetCounter, models.Count] = target;
targetCounter++;
}
alglib.linearmodel lm = new alglib.linearmodel();
alglib.lrreport ar = new alglib.lrreport();
double[] coefficients;
int retVal = 1;
alglib.lrbuildz(inputMatrix, rows, features, out retVal, out lm, out ar);
if (retVal != 1) throw new ArgumentException("Error in calculation of linear regression solution");
alglib.lrunpack(lm, out coefficients, out features);
var ensembleModel = new RegressionEnsembleModel(models, coefficients.Take(models.Count)) { AverageModelEstimates = false };
var ensembleSolution = (IRegressionEnsembleSolution)ensembleModel.CreateRegressionSolution(problemData); return ensembleSolution;
}
