public static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double[] ground_truth = Load.load_labels("../data/label_train_twoclass.dat");
Random RandomNumber = new Random();
double[] predicted = new double[ground_truth.Length];
for (int i = 0; i < ground_truth.Length; i++)
{
predicted[i] = RandomNumber.NextDouble();
}
BinaryLabels ground_truth_labels = new BinaryLabels(ground_truth);
BinaryLabels predicted_labels = new BinaryLabels(predicted);
ContingencyTableEvaluation base_evaluator = new ContingencyTableEvaluation();
base_evaluator.evaluate(predicted_labels, ground_truth_labels);
AccuracyMeasure evaluator1 = new AccuracyMeasure();
double accuracy = evaluator1.evaluate(predicted_labels, ground_truth_labels);
ErrorRateMeasure evaluator2 = new ErrorRateMeasure();
double errorrate = evaluator2.evaluate(predicted_labels, ground_truth_labels);
BALMeasure evaluator3 = new BALMeasure();
double bal = evaluator3.evaluate(predicted_labels, ground_truth_labels);
WRACCMeasure evaluator4 = new WRACCMeasure();
double wracc = evaluator4.evaluate(predicted_labels, ground_truth_labels);
F1Measure evaluator5 = new F1Measure();
double f1 = evaluator5.evaluate(predicted_labels, ground_truth_labels);
CrossCorrelationMeasure evaluator6 = new CrossCorrelationMeasure();
double crosscorrelation = evaluator6.evaluate(predicted_labels, ground_truth_labels);
RecallMeasure evaluator7 = new RecallMeasure();
double recall = evaluator7.evaluate(predicted_labels, ground_truth_labels);
PrecisionMeasure evaluator8 = new PrecisionMeasure();
double precision = evaluator8.evaluate(predicted_labels, ground_truth_labels);
SpecificityMeasure evaluator9 = new SpecificityMeasure();
double specificity = evaluator9.evaluate(predicted_labels, ground_truth_labels);
Console.Write("{0}, {1}, {2}, {3}, {4}, {5}, {6}, {7}, {8}\n", accuracy, errorrate, bal, wracc, f1, crosscorrelation, recall, precision, specificity);
modshogun.exit_shogun();
}
public static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double[] ground_truth = Load.load_labels("../data/label_train_twoclass.dat");
Random RandomNumber = new Random();
double[] predicted = new double[ground_truth.Length];
for (int i = 0; i < ground_truth.Length; i++) {
predicted[i] = RandomNumber.NextDouble();
}
BinaryLabels ground_truth_labels = new BinaryLabels(ground_truth);
BinaryLabels predicted_labels = new BinaryLabels(predicted);
ContingencyTableEvaluation base_evaluator = new ContingencyTableEvaluation();
base_evaluator.evaluate(predicted_labels,ground_truth_labels);
AccuracyMeasure evaluator1 = new AccuracyMeasure();
double accuracy = evaluator1.evaluate(predicted_labels,ground_truth_labels);
ErrorRateMeasure evaluator2 = new ErrorRateMeasure();
double errorrate = evaluator2.evaluate(predicted_labels,ground_truth_labels);
BALMeasure evaluator3 = new BALMeasure();
double bal = evaluator3.evaluate(predicted_labels,ground_truth_labels);
WRACCMeasure evaluator4 = new WRACCMeasure();
double wracc = evaluator4.evaluate(predicted_labels,ground_truth_labels);
F1Measure evaluator5 = new F1Measure();
double f1 = evaluator5.evaluate(predicted_labels,ground_truth_labels);
CrossCorrelationMeasure evaluator6 = new CrossCorrelationMeasure();
double crosscorrelation = evaluator6.evaluate(predicted_labels,ground_truth_labels);
RecallMeasure evaluator7 = new RecallMeasure();
double recall = evaluator7.evaluate(predicted_labels,ground_truth_labels);
PrecisionMeasure evaluator8 = new PrecisionMeasure();
double precision = evaluator8.evaluate(predicted_labels,ground_truth_labels);
SpecificityMeasure evaluator9 = new SpecificityMeasure();
double specificity = evaluator9.evaluate(predicted_labels,ground_truth_labels);
Console.Write("{0}, {1}, {2}, {3}, {4}, {5}, {6}, {7}, {8}\n", accuracy, errorrate, bal, wracc, f1, crosscorrelation, recall, precision, specificity);
modshogun.exit_shogun();
}
static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
DoubleMatrix ground_truth = Load.load_labels("../data/label_train_twoclass.dat");
DoubleMatrix predicted = randn(1, ground_truth.Length);
Labels ground_truth_labels = new Labels(ground_truth);
Labels predicted_labels = new Labels(predicted);
ContingencyTableEvaluation base_evaluator = new ContingencyTableEvaluation();
base_evaluator.evaluate(predicted_labels,ground_truth_labels);
AccuracyMeasure evaluator1 = new AccuracyMeasure();
double accuracy = evaluator1.evaluate(predicted_labels,ground_truth_labels);
ErrorRateMeasure evaluator2 = new ErrorRateMeasure();
double errorrate = evaluator2.evaluate(predicted_labels,ground_truth_labels);
BALMeasure evaluator3 = new BALMeasure();
double bal = evaluator3.evaluate(predicted_labels,ground_truth_labels);
WRACCMeasure evaluator4 = new WRACCMeasure();
double wracc = evaluator4.evaluate(predicted_labels,ground_truth_labels);
F1Measure evaluator5 = new F1Measure();
double f1 = evaluator5.evaluate(predicted_labels,ground_truth_labels);
CrossCorrelationMeasure evaluator6 = new CrossCorrelationMeasure();
double crosscorrelation = evaluator6.evaluate(predicted_labels,ground_truth_labels);
RecallMeasure evaluator7 = new RecallMeasure();
double recall = evaluator7.evaluate(predicted_labels,ground_truth_labels);
PrecisionMeasure evaluator8 = new PrecisionMeasure();
double precision = evaluator8.evaluate(predicted_labels,ground_truth_labels);
SpecificityMeasure evaluator9 = new SpecificityMeasure();
double specificity = evaluator9.evaluate(predicted_labels,ground_truth_labels);
Console.Write("{0:F}, {1:F}, {2:F}, {3:F}, {4:F}, {5:F}, {6:F}, {7:F}, {8:F}\n", accuracy, errorrate, bal, wracc, f1, crosscorrelation, recall, precision, specificity);
modshogun.exit_shogun();
}
internal static HandleRef getCPtr(SpecificityMeasure obj) {
return (obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr;
}
internal static HandleRef getCPtr(SpecificityMeasure obj)
{
return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr);
}
