/// <summary>
        /// Вероятности принадлежности к классу
        /// </summary>
        /// <param name="vect"></param>
        /// <param name="sm"></param>
        void GetProbability(double[] vect, SModel sm)
        {
            for (int i = 0; i < vect.Length; i++)
            {
                sm[i].pr = DistributionFunc.GaussNorm1(vect[i], sm[i]._e, sm[i]._sco);
            }

            sm.CalculateProb();
        }
        /// <summary>
        ///
        /// </summary>
        /// <param name="dataset"></param>
        /// <returns></returns>
        public static Vector ImportanceSign(Vector[] dataset)
        {
            Vector   dispers = Statistic.EnsembleDispersion(dataset);
            double   m       = Statistic.ExpectedValue(dispers);
            double   std     = Statistic.Std(dispers);
            Vector   Y       = DistributionFunc.GaussNorm1(dispers, m, std);
            Vector   X       = MathFunc.GenerateTheSequence(0, 1, Y.N);
            RBFGauss regr    = new RBFGauss(X, Y, 25);

            return(regr.Predict(X));
        }