使用C＃和「Accord.NET」進行非線性支持向量迴歸

Question

Accord中，我應該如何使用C＃進行非線性向量回歸？ 由於 （traininginputs雙[] []和trainingoutput 雙[]不是int []）

Answer 1

Accord.NET提供了在SequentialMinimalOptimizationRegression類迴歸問題支持向量機學習算法。有一個example application for this topic in the sample application's wiki page。

下面是關於如何使用它的一個例子：

// 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);