Example #1
0
        //Function that takes the computed confusion matrices
        //and calculates:
        //Average Accuracy, Average Accuracy per class, Average Recall per class
        public static Double[,] ProcessStatistics(ConfusionMatrix[,] data)
        {
            Double[,] average = new Double[4, 5];
            //For each algorithm
            for (int i = 0; i < 4; i++)
            {
                //For each confusion matrix
                for (int j = 0; j < 5; j++)
                {
                    //Calculate
                    average[i, 0] += data[i, j].Accuracy;                                                                                //General accuracy
                    average[i, 1] += data[i, j].PredictedPositives / GetNonZero(data[i, j].ActualPositives + data[i, j].FalsePositives); //Accuracy for class 1
                    average[i, 2] += data[i, j].PredictedNegatives / GetNonZero(data[i, j].ActualNegatives + data[i, j].FalseNegatives); //Accuracy for class 2
                    average[i, 3] += data[i, j].TruePositives / GetNonZero(data[i, j].TruePositives + data[i, j].FalseNegatives);        //Recall for class 1
                    average[i, 4] += data[i, j].TrueNegatives / GetNonZero(data[i, j].TrueNegatives + data[i, j].FalsePositives);        //Recall fro class 2
                }
            }

            return(average.Apply(x => x / 5));
        }