Пример #1
0
        private static double[] tethaGradientValue(Individual tetha2, List<Individual> population)
        {
            Individual result = new Individual(tetha2 / Math.Pow(sigma, 2)); ;
            for (int row = 0; row < population.Count; row++)
            {
                for (int col = row; col < population.Count; col++)
                {
                    if (row == col) continue;
                    Individual secondTerm = new Individual(new Individual(population[row] - population[col]) * (double)(numberOfGames - 2 * population[row].Labels[col]));
                    result = new Individual(result + secondTerm);
                    Individual difference = new Individual(population[row] - population[col]);
                    double vValue = difference.DotProduct(tetha2.Weights);
                    Individual gOfXY = new Individual(difference * ((Math.Exp(vValue) - Math.Exp(-vValue)) / (Math.Exp(vValue) + Math.Exp(-vValue))));
                    result = new Individual(result + gOfXY);

                }
            }
            return result.Weights;
        }
Пример #2
0
 private static double xStarFunctionValue(Individual xStar2, List<Individual> population)
 {
     Individual result = new Individual(xStar2 * (double)population.Count);
     Individual sum = new Individual(new double[numberOfFeatures]);
     double gOfXY = 0;
     for (int index = 1; index < population.Count; index++)
     {
         sum = new Individual(sum + population[index]);
         Individual newIndiv = new Individual(xStar2 - population[index]);
         double localValue = newIndiv.DotProduct(tetha.Weights);
         gOfXY += Math.Log(Math.Exp(localValue) + Math.Exp(-localValue));
     }
     result = new Individual(sum - result);
     return result.DotProduct(tetha.Weights) + gOfXY;
 }
Пример #3
0
        private static double tethaFunctionValue(Individual tetha2, List<Individual> population)
        {
            double result = 0;
            result += Math.Pow(tetha2.EuclideanNorm(),2) / 2 * Math.Pow(sigma, 2);

            for (int row = 0; row < population.Count; row++)
            {
                for (int col = row; col < population.Count; col++)
                {
                    if (row == col) continue;
                    Individual newIndiv = new Individual(population[row] - population[col]);
                    double localValue = newIndiv.DotProduct(tetha2.Weights);
                    double gOfXY = Math.Log(Math.Exp(localValue) + Math.Exp(-localValue));
                    localValue = localValue * (double)(numberOfGames - 2 * population[row].Labels[col]) + (double)numberOfGames * gOfXY;
                    result += localValue;

                }
            }
            return result;
        }