Accord.NET为示例应用程序Wiki页面.

Accord.NET provides a Support Vector Machine learning algorithm for regression problems in the SequentialMinimalOptimizationRegression class. There is an example application for this topic in the sample application's wiki page.

以下是使用方法的示例:

Here is an example on how to use it:

// Example regression problem. Suppose we are trying
// to model the following equation: f(x, y) = 2x + y

double[][] inputs = // (x, y)
{
    new double[] { 0,  1 }, // 2*0 + 1 =  1
    new double[] { 4,  3 }, // 2*4 + 3 = 11
    new double[] { 8, -8 }, // 2*8 - 8 =  8
    new double[] { 2,  2 }, // 2*2 + 2 =  6
    new double[] { 6,  1 }, // 2*6 + 1 = 13
    new double[] { 5,  4 }, // 2*5 + 4 = 14
    new double[] { 9,  1 }, // 2*9 + 1 = 19
    new double[] { 1,  6 }, // 2*1 + 6 =  8
};

double[] outputs = // f(x, y)
{
    1, 11, 8, 6, 13, 14, 20, 8
};

// Create the sequential minimal optimization teacher
var learn = new SequentialMinimalOptimizationRegression<Polynomial>()
{
    Kernel = new Polynomial(degree: 2)
}

// Use the teacher to learn a new machine
var svm = teacher.Learn(inputs, outputs);

// Compute the answer for one particular example
double fxy = machine.Transform(inputs[0]); // 1.0003849827673186

// Compute the answer for all examples 
double[] fxys = machine.Transform(inputs);