Inheritance: INeighborhoodFunction
        /// <summary>
        /// Create a LMA trainer.
        /// </summary>
        ///
        /// <param name="method">The method to use.</param>
        /// <param name="training">The training data to use.</param>
        /// <param name="argsStr">The arguments to use.</param>
        /// <returns>The newly created trainer.</returns>
        public IMLTrain Create(IMLMethod method,
                              IMLDataSet training, String argsStr)
        {
            if (!(method is SupportVectorMachine))
            {
                throw new EncogError(
                    "Neighborhood training cannot be used on a method of type: "
                    + method.GetType().FullName);
            }

            IDictionary<String, String> args = ArchitectureParse.ParseParams(argsStr);
            var holder = new ParamsHolder(args);

            double learningRate = holder.GetDouble(
                MLTrainFactory.PropertyLearningRate, false, 0.7d);
            String neighborhoodStr = holder.GetString(
                MLTrainFactory.PropertyNeighborhood, false, "rbf");
            String rbfTypeStr = holder.GetString(
                MLTrainFactory.PropertyRBFType, false, "gaussian");

            RBFEnum t;

            if (rbfTypeStr.Equals("Gaussian", StringComparison.InvariantCultureIgnoreCase))
            {
                t = RBFEnum.Gaussian;
            }
            else if (rbfTypeStr.Equals("Multiquadric", StringComparison.InvariantCultureIgnoreCase))
            {
                t = RBFEnum.Multiquadric;
            }
            else if (rbfTypeStr.Equals("InverseMultiquadric", StringComparison.InvariantCultureIgnoreCase))
            {
                t = RBFEnum.InverseMultiquadric;
            }
            else if (rbfTypeStr.Equals("MexicanHat", StringComparison.InvariantCultureIgnoreCase))
            {
                t = RBFEnum.MexicanHat;
            }
            else
            {
                t = RBFEnum.Gaussian;
            }

            INeighborhoodFunction nf = null;

            if (neighborhoodStr.Equals("bubble", StringComparison.InvariantCultureIgnoreCase))
            {
                nf = new NeighborhoodBubble(1);
            }
            else if (neighborhoodStr.Equals("rbf", StringComparison.InvariantCultureIgnoreCase))
            {
                String str = holder.GetString(
                    MLTrainFactory.PropertyDimensions, true, null);
                int[] size = NumberList.FromListInt(CSVFormat.EgFormat, str);
                nf = new NeighborhoodRBF(size, t);
            }
            else if (neighborhoodStr.Equals("rbf1d", StringComparison.InvariantCultureIgnoreCase))
            {
                nf = new NeighborhoodRBF1D(t);
            }
            if (neighborhoodStr.Equals("single", StringComparison.InvariantCultureIgnoreCase))
            {
                nf = new NeighborhoodSingle();
            }

            var result = new BasicTrainSOM((SOMNetwork) method,
                                           learningRate, training, nf);

            if (args.ContainsKey(MLTrainFactory.PropertyIterations))
            {
                int plannedIterations = holder.GetInt(
                    MLTrainFactory.PropertyIterations, false, 1000);
                double startRate = holder.GetDouble(
                    MLTrainFactory.PropertyStartLearningRate, false, 0.05d);
                double endRate = holder.GetDouble(
                    MLTrainFactory.PropertyEndLearningRate, false, 0.05d);
                double startRadius = holder.GetDouble(
                    MLTrainFactory.PropertyStartRadius, false, 10);
                double endRadius = holder.GetDouble(
                    MLTrainFactory.PropertyEndRadius, false, 1);
                result.SetAutoDecay(plannedIterations, startRate, endRate,
                                    startRadius, endRadius);
            }

            return result;
        }
Example #2
0
 public IMLTrain Create(IMLMethod method, IMLDataSet training, string argsStr)
 {
     IDictionary<string, string> dictionary;
     ParamsHolder holder;
     double num;
     string str;
     string str2;
     RBFEnum mexicanHat;
     INeighborhoodFunction function;
     string str3;
     int[] numArray;
     BasicTrainSOM nsom;
     int num2;
     double num3;
     double num4;
     double num6;
     if (method is SupportVectorMachine)
     {
         dictionary = ArchitectureParse.ParseParams(argsStr);
         holder = new ParamsHolder(dictionary);
         num = holder.GetDouble("LR", false, 0.7);
         str = holder.GetString("NEIGHBORHOOD", false, "rbf");
         if (2 != 0)
         {
             goto Label_03DF;
         }
         goto Label_039F;
     }
     goto Label_03F4;
     Label_0083:
     num4 = holder.GetDouble("END_LR", false, 0.05);
     double startRadius = holder.GetDouble("START_RADIUS", false, 10.0);
     if ((((uint) num4) + ((uint) num4)) > uint.MaxValue)
     {
         return nsom;
     }
     if ((((uint) num3) + ((uint) num2)) <= uint.MaxValue)
     {
         num6 = holder.GetDouble("END_RADIUS", false, 1.0);
         nsom.SetAutoDecay(num2, num3, num4, startRadius, num6);
         return nsom;
     }
     Label_00E4:
     if (4 == 0)
     {
         if ((((uint) num3) + ((uint) num2)) > uint.MaxValue)
         {
             goto Label_0292;
         }
         goto Label_02F8;
     }
     Label_00EE:
     nsom = new BasicTrainSOM((SOMNetwork) method, num, training, function);
     do
     {
         if (dictionary.ContainsKey("ITERATIONS"))
         {
             do
             {
                 num2 = holder.GetInt("ITERATIONS", false, 0x3e8);
                 num3 = holder.GetDouble("START_LR", false, 0.05);
             }
             while ((((uint) num3) | 15) == 0);
             goto Label_0083;
         }
     }
     while ((((uint) num6) | 0xff) == 0);
     if (0 == 0)
     {
         if ((((uint) num3) + ((uint) num3)) >= 0)
         {
             return nsom;
         }
         goto Label_03F4;
     }
     if ((((uint) num2) - ((uint) startRadius)) <= uint.MaxValue)
     {
         goto Label_00E4;
     }
     goto Label_0083;
     Label_0184:
     if (!str.Equals("single", StringComparison.InvariantCultureIgnoreCase))
     {
         goto Label_00EE;
     }
     function = new NeighborhoodSingle();
     if ((((uint) num6) - ((uint) num3)) >= 0)
     {
         if ((((uint) num) - ((uint) startRadius)) >= 0)
         {
             goto Label_00E4;
         }
         goto Label_0324;
     }
     if ((((uint) num2) & 0) == 0)
     {
         goto Label_0233;
     }
     Label_01E2:
     while (!str.Equals("rbf1d", StringComparison.InvariantCultureIgnoreCase))
     {
         if (0 == 0)
         {
             if ((((uint) num3) - ((uint) num6)) >= 0)
             {
                 goto Label_0184;
             }
             goto Label_0233;
         }
     }
     function = new NeighborhoodRBF1D(mexicanHat);
     if ((((uint) num2) + ((uint) num)) >= 0)
     {
         if (((uint) num6) < 0)
         {
             goto Label_01E2;
         }
         goto Label_0184;
     }
     if (((uint) num2) < 0)
     {
         goto Label_03DF;
     }
     goto Label_01E2;
     Label_0233:
     function = new NeighborhoodRBF(numArray, mexicanHat);
     goto Label_0184;
     Label_0243:
     if (!str.Equals("rbf", StringComparison.InvariantCultureIgnoreCase))
     {
         if ((((uint) num2) & 0) != 0)
         {
             goto Label_03DF;
         }
         goto Label_01E2;
     }
     Label_0292:
     str3 = holder.GetString("DIM", true, null);
     if ((((uint) num3) + ((uint) num)) > uint.MaxValue)
     {
         goto Label_0292;
     }
     numArray = NumberList.FromListInt(CSVFormat.EgFormat, str3);
     if ((((uint) num6) & 0) == 0)
     {
         goto Label_0233;
     }
     goto Label_0243;
     Label_02F8:
     if (str.Equals("bubble", StringComparison.InvariantCultureIgnoreCase))
     {
         function = new NeighborhoodBubble(1);
         goto Label_0184;
     }
     if ((((uint) num3) & 0) == 0)
     {
         goto Label_0243;
     }
     goto Label_0292;
     Label_0324:
     function = null;
     goto Label_02F8;
     Label_0362:
     mexicanHat = RBFEnum.Multiquadric;
     goto Label_0324;
     Label_039F:
     mexicanHat = RBFEnum.Gaussian;
     goto Label_0324;
     Label_03DF:
     str2 = holder.GetString("RBF_TYPE", false, "gaussian");
     if (str2.Equals("Gaussian", StringComparison.InvariantCultureIgnoreCase))
     {
         goto Label_039F;
     }
     if (((uint) startRadius) <= uint.MaxValue)
     {
         if (str2.Equals("Multiquadric", StringComparison.InvariantCultureIgnoreCase))
         {
             goto Label_0362;
         }
         if (!str2.Equals("InverseMultiquadric", StringComparison.InvariantCultureIgnoreCase) || ((((uint) num2) + ((uint) num2)) < 0))
         {
             if (str2.Equals("MexicanHat", StringComparison.InvariantCultureIgnoreCase))
             {
                 mexicanHat = RBFEnum.MexicanHat;
             }
             else
             {
                 mexicanHat = RBFEnum.Gaussian;
             }
             goto Label_0324;
         }
     }
     else if (((uint) num3) <= uint.MaxValue)
     {
         goto Label_0362;
     }
     if ((((uint) num3) - ((uint) num3)) <= uint.MaxValue)
     {
         mexicanHat = RBFEnum.InverseMultiquadric;
         goto Label_0324;
     }
     goto Label_00E4;
     Label_03F4:
     throw new EncogError("Neighborhood training cannot be used on a method of type: " + method.GetType().FullName);
 }