@Override public void assign(double[] point, double[] fit) { double total = 0; for (int i = 0; i < mixture.size(); i++) { total += fit[i] = glm.getLikelihood(i).likelihood(point); } for (int i = 0; i < mixture.size(); i++) { fit[i] /= total; } }
@Override public int assign(double[] point) { int indexBest = -1; double scoreBest = 0; for (int i = 0; i < mixture.size(); i++) { double score = glm.getLikelihood(i).likelihood(point); if( score > scoreBest ) { scoreBest = score; indexBest = i; } } return indexBest; }
@Override public void assign(double[] point, double[] fit) { double total = 0; for (int i = 0; i < mixture.size(); i++) { total += fit[i] = glm.getLikelihood(i).likelihood(point); } for (int i = 0; i < mixture.size(); i++) { fit[i] /= total; } }
@Override public int assign(double[] point) { int indexBest = -1; double scoreBest = 0; for (int i = 0; i < mixture.size(); i++) { double score = glm.getLikelihood(i).likelihood(point); if( score > scoreBest ) { scoreBest = score; indexBest = i; } } return indexBest; }
GaussianLikelihoodManager.Likelihood g = likelihoodManager.getLikelihood(j); double likelihood = g.likelihood(p.point); total += p.weights.data[j] = likelihood;
GaussianLikelihoodManager.Likelihood g = likelihoodManager.getLikelihood(j); double likelihood = g.likelihood(p.point); total += p.weights.data[j] = likelihood;
double foundA = manager.getLikelihood(0).likelihood(p); double chiSqA = manager.getLikelihood(0).getChisq(); double foundB = manager.getLikelihood(1).likelihood(p); double chiSqB = manager.getLikelihood(1).getChisq();