public void ReceiverOperatingCharacteristicConstructorTest3()
{
// This example shows how to measure the accuracy of a
// binary classifier using a ROC curve. For this example,
// we will be creating a Support Vector Machine trained
// on the following instances:
double[][] inputs =
{
// Those are from class -1
new double[] { 2, 4, 0 },
new double[] { 5, 5, 1 },
new double[] { 4, 5, 0 },
new double[] { 2, 5, 5 },
new double[] { 4, 5, 1 },
new double[] { 4, 5, 0 },
new double[] { 6, 2, 0 },
new double[] { 4, 1, 0 },
// Those are from class +1
new double[] { 1, 4, 5 },
new double[] { 7, 5, 1 },
new double[] { 2, 6, 0 },
new double[] { 7, 4, 7 },
new double[] { 4, 5, 0 },
new double[] { 6, 2, 9 },
new double[] { 4, 1, 6 },
new double[] { 7, 2, 9 },
};
int[] outputs =
{
-1, -1, -1, -1, -1, -1, -1, -1, // first eight from class -1
+1, +1, +1, +1, +1, +1, +1, +1 // last eight from class +1
};
// Create a linear Support Vector Machine with 3 inputs
var machine = new SupportVectorMachine(inputs: 3);
// Create the sequential minimal optimization teacher
var learn = new SequentialMinimalOptimization(machine, inputs, outputs)
{
Complexity = 1
};
// Run the learning algorithm
double error = learn.Run();
// Extract the input labels predicted by the machine
double[] predicted = new double[inputs.Length];
for (int i = 0; i < predicted.Length; i++)
predicted[i] = machine.Score(inputs[i]);
// Create a new ROC curve to assess the performance of the model
var roc = new ReceiverOperatingCharacteristic(outputs, predicted);
roc.Compute(100); // Compute a ROC curve with 100 points
/*
// Generate a connected scatter plot for the ROC curve and show it on-screen
ScatterplotBox.Show(roc.GetScatterplot(includeRandom: true), nonBlocking: true)
.SetSymbolSize(0) // do not display data points
.SetLinesVisible(true) // show lines connecting points
.SetScaleTight(true) // tighten the scale to points
.WaitForClose();
*/
Assert.AreEqual(0.25, error);
Assert.AreEqual(0.78125, roc.Area);
// Assert.AreEqual(0.1174774, roc.StandardError, 1e-6); HanleyMcNeil
// Assert.AreEqual(0.11958120746409709, roc.StandardError, 1e-6);
Assert.AreEqual(0.132845321574701, roc.StandardError, 1e-6);
}
