public Matrix PredictProbability(Matrix input)
{
var jointLogLikelihood = new Vector[ClassPriors.Count()];
for (int i = 0; i < ClassPriors.Count(); i++)
{
var kvp = ClassPriors.ElementAt(i);
var jointi = System.Math.Log(kvp.Value);
var nij = Sigma.GetRowVector(i).Multiply(System.Math.PI).Multiply(2.0).Log().Sum().GetNumber() * -0.5;
var res = input.Substract(Theta.GetRowVector(i)).Pow(2).Div(Sigma.GetRowVector(i)).SumAllRows().Multiply(-0.5).Sum(nij);
jointLogLikelihood[i] = res.Sum(jointi);
}
Matrix jointLogLikelihoodMatrix = jointLogLikelihood;
jointLogLikelihoodMatrix = jointLogLikelihoodMatrix.Transpose();
var logProbX = jointLogLikelihoodMatrix.Logsumexp();
return(jointLogLikelihoodMatrix.Substract(logProbX).Exp());
}
