Exemple #1
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        public static DataSet ReadData(string fileName)
        {
            TextReader textReader = new StreamReader(@fileName);

            string temp = textReader.ReadLine().Trim();
            int total = int.Parse(temp);

            temp = textReader.ReadLine().Trim();
            int[] tempIntArray = stringToIntArray(temp, new char[] { '\t', ' ' });

            int numberOfInputNodes = tempIntArray[0];
            int numberOfOutputNodes = tempIntArray[1];

            double [,] inputdata = new double[total, numberOfInputNodes];
            double [,] desiredOutputs = new double [total, numberOfOutputNodes];

            for (int i = 0; i < total; i++)
            {
                temp = textReader.ReadLine().Trim();
                double[] tempDoubleArray = stringToDoubleArray(temp, new char[] {'\t', ' ' });
                for (int j = 0; j < numberOfInputNodes; j++)
                {
                    inputdata[i, j] = tempDoubleArray[j];
                }

                for (int j = 0; j < numberOfOutputNodes; j++)
                {
                    desiredOutputs[i, j] = tempDoubleArray[numberOfInputNodes + j];
                }
            }

            DataSet result = new DataSet(inputdata, desiredOutputs);

            return result;
        }
Exemple #2
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 public PoptvrSystem(DataSet dataset, ClusterSetting clusterSetting, ClusterFacadeInterface clusterFacade, Settings settings)
 {
     this.dataset = dataset;
     this.clusterSetting = clusterSetting;
     this.clusterFacade = clusterFacade;
     this.appConfig = new AppConfig(settings);
 }
Exemple #3
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        public PoptvrModel(DataSet dataset, ClusterSetting clusterSetting)
        {
            this.dataset = dataset;
            this.clusterSetting = clusterSetting;

            this.numberOfInputs = this.dataset.NumberOfInputNodes;
            this.numberOfOutputs = this.dataset.NumberOfOutputNodes;

            this.inputClusterSize = this.clusterSetting.InputClusterSize;
            this.outputClusterSize = this.clusterSetting.OutputClusterSize;

            buildRULES();
	        buildPOPTVR();
        }  
Exemple #4
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 public MlvqFacade(DataSet dataset, ClusterSetting clusterSetting)
 {
     this.clusterSetting = clusterSetting;
     this.dataset = dataset;
 }
Exemple #5
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        // inclusive "from", exclusive "to"
        public DataSet subset(int from, int to)
        {
            double[,] inputdata = new double[to - from, this.numberOfInputNodes];
            double[,] desiredOutputs = new double [to - from, this.numberOfOutputNodes];

            for (int i = 0; i < to - from; i++)
            {
                for (int j = 0; j < this.numberOfInputNodes; j++)
                {
                    inputdata[i,j] = this.inputdata[i + from,j];
                }

                for (int j = 0; j < this.numberOfOutputNodes; j++)
                {
                    desiredOutputs[i, j] = this.desiredOutputs[i + from, j];
                }
            }

            DataSet result = new DataSet(inputdata, desiredOutputs);

            return result;
        }
Exemple #6
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        public static string POPTest(PoptvrModel poptvr, DataSet dataset)
        {
            Console.WriteLine("POPTest ....");

            string resultString = "";
            int correct = 0;

            int[] ruleNodes = new int[(int)Math.Pow(poptvr.inputClusterSize, dataset.NumberOfInputNodes)];
            int[] classTotal = new int[dataset.NumberOfOutputNodes];
            int[] classCorrect = new int[dataset.NumberOfOutputNodes];

            for (int i = 0; i < dataset.TotalNumberOfRecords; i++)
            {
                bool correctFlag = false;

                poptvr.forwardFeed(SystemFunctions.getArrayAtRow(dataset.Inputdata, i));
                poptvr.maxRuleNode(ruleNodes);

                double max = poptvr.OutputLayer[0].Output;
                int maxIndex = 0;
                for (int j = 0; j < dataset.NumberOfOutputNodes; j++)
                {
                    resultString += String.Format("{0:F3}\t", poptvr.OutputLayer[j].Output);
                    if (max < poptvr.OutputLayer[j].Output)
                    {
                        max = poptvr.OutputLayer[j].Output;
                        maxIndex = j;
                    }
                }

                for (int j = 0; j < dataset.NumberOfOutputNodes; j++)
                {
                    // calculate the total no. in each class
                    if (dataset.DesiredOutputs[i, j] == 1.0)
                    {
                        classTotal[j]++;
                    }
                    // calculate the correct no. in each class, overall correct
                    if (j == maxIndex)
                    {
                        if (dataset.DesiredOutputs[i, j] == 1.0)
                        {
                            correct++;
                            classCorrect[j]++;
                            correctFlag = true;
                        }
                    }
                }

                if (correctFlag)
                {
                    resultString += "\n";
                }
                else
                {
                    resultString += "X\n";
                }
            }

            for (int i = 0; i < dataset.NumberOfOutputNodes; i++)
            {
                resultString += String.Format("Class [{0:D}]:\t{1:F3}\tpercent\n", i, ((double)classCorrect[i] * 100.0) / (double)classTotal[i]);
            }

            resultString += String.Format("Overall:\t {0:F3}\tpercent\n", (correct * 100.0) / dataset.TotalNumberOfRecords);

            int totalRulesFired = 0;
            for (int i = 0; i < ruleNodes.Length; i++)
            {
                if (ruleNodes[i] != 0)
                {
                    totalRulesFired++;
                }

                resultString += String.Format("ruleNode {0:D}:\t{1:D}\n", i, ruleNodes[i]);
            }

            resultString += String.Format("Total Rules Fired:\t{0:D}\n", totalRulesFired);

            return resultString;
        }
Exemple #7
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 public void popLearn(DataSet dataset)
 {
     this.dataset = dataset;
     popLearn();
 }
Exemple #8
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        public static PoptvrModel RuleReduction(PoptvrModel poptvr, DataSet dataset, AppConfig appConfig)
        {
            Console.WriteLine("Start RSPOP reduction ..."); 

            double[] CO = new double[dataset.NumberOfOutputNodes * poptvr.OutputClusterSize];
            double[] COr = new double[dataset.NumberOfOutputNodes * poptvr.OutputClusterSize];

            string res = "Removed from total " + poptvr.RuleLayer.Length + "\n";

            for (int k = 0; k < poptvr.RuleLayer.Length; k++)
            {          


                for (int i = 0; i < dataset.TotalNumberOfRecords; i++)
                {
                    Console.Write("at condition " + k + "\t" + "record " + i + "\n");

                    poptvr.forwardFeed(SystemFunctions.getArrayAtRow(dataset.Inputdata, i));
                    for (int j = 0; j < dataset.NumberOfOutputNodes * poptvr.OutputClusterSize; j++)
                    {
                        CO[j] = poptvr.ConsequenceLayer[j].Output;
                    }
               
                    for (int l = 0; l < poptvr.InputClusterSize; l++)
                    {
                        bool deterioration = false;
                        poptvr.RuleLayer[k].PointBlocked = true;
                        poptvr.RuleLayer[k].PointBlockedAt = l;

                        poptvr.forwardFeed(SystemFunctions.getArrayAtRow(dataset.Inputdata, i));
                        for (int j = 0; j < dataset.NumberOfOutputNodes * poptvr.OutputClusterSize; j++)
                        {
                            COr[j] = poptvr.ConsequenceLayer[j].Output;

                            if (COr[j] < CO[j])
                            {
                                deterioration = true;
                            }
                            else
                            {

                                for (int m = 0; m < CO.Length; m++)
                                {
                                    if (COr[j] > CO[m])
                                    {
                                        deterioration = true;
                                        break;
                                    }
                                }
                            }

                            if (deterioration)
                            {
                                break;
                            }
                        }

                        if (!deterioration)
                        {
                            res += (l + " is remove at " + k + "\n");
                            poptvr.RuleLayer[k].PointBlocked = false;
                        }
                        if (deterioration)
                        {
                            poptvr.RuleLayer[k].PointBlocked = false;
                        }
                    }          
                }

            }

            FileWriter fileWriter = new FileWriter(appConfig);
            fileWriter.WriteToFile(appConfig.getOutputFolder() + "Removed Rule.txt", res);
            return poptvr;
        }
Exemple #9
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 public void PopTest(DataSet dataset)
 {
     string result = PoptvrModel.POPTest(this.poptvr, dataset);
     FileWriter fileWriter = new FileWriter(this.appConfig);
     fileWriter.WritePopTestOutput(result);
 }
Exemple #10
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 public PoptvrSystem(DataSet dataset, ClusterSetting clusterSetting, ClusterFacadeInterface clusterFacade)
 {
     this.dataset = dataset;
     this.clusterSetting = clusterSetting;
     this.clusterFacade = clusterFacade;
 }