.net随笔-vb.net Accord.Net机器学习之SVM分类

线性核分类

 Imports Accord.Controls
    Imports Accord.IO
    Imports Accord.Math
    Imports Accord.Statistics.Distributions.Univariate
    Imports Accord.MachineLearning.VectorMachines.Learning
    Imports Accord.Statistics
    Imports System
    
    Public Class Form1
    
        'SVM线性分类
        '使用Accord.IO里的的excel读取类
        Dim table As DataTable = New ExcelReader("E:\pro\books\AI_.net\src\AI_learn\learnai-1\data\examples.xls").GetWorksheet("Classification - Yin Yang")
        Private Sub Button1_Click(sender As Object, e As EventArgs) Handles Button1.Click
    
            NaiveBayes()
        End Sub
        Private Sub NaiveBayes()
            '读取样本
            ' 转换datatable为输入输出数组
            Dim sample As Double()() = table.ToJagged(Of Double)("X", "Y")
            Dim outs As Integer() = table.Columns("G").ToArray(Of Integer)()
    
    
    
    
            Dim trainer As New LinearCoordinateDescent()
    
            Dim svm = trainer.Learn(sample, outs)
    
            Dim predictResult As Boolean() = svm.Decide(sample)
    
    
    
            Dim zeroOneAnswers As Integer() = predictResult.ToZeroOne()
    
    
    
    
    
            ScatterplotBox.Show("实际结果", sample, outs)
            ScatterplotBox.Show("SVM预测结果", sample, zeroOneAnswers).Hold()
    
    
    
    
    
    
        End Sub
    End Class

效果如下

非线性高斯核分类

Imports Accord.Controls
Imports Accord.IO
Imports Accord.Math
Imports Accord.Statistics.Distributions.Univariate
Imports Accord.MachineLearning.VectorMachines.Learning
Imports Accord.Statistics
Imports Accord.Statistics.Kernels
Imports System

Public Class Form1

    'SVM非线性核
    '使用Accord.IO里的的excel读取类
    Dim table As DataTable = New ExcelReader("E:\pro\books\AI_.net\src\AI_learn\data\examples.xls").GetWorksheet("Classification - Yin Yang")
    Private Sub Button1_Click(sender As Object, e As EventArgs) Handles Button1.Click

        NaiveBayes()
    End Sub
    Private Sub NaiveBayes()
        '读取样本
        ' 转换datatable为输入输出数组
        Dim sample As Double()() = table.ToJagged(Of Double)("X", "Y")
        Dim outs As Integer() = table.Columns("G").ToArray(Of Integer)()




        Dim trainer As New SequentialMinimalOptimization(Of Gaussian)
        trainer.UseComplexityHeuristic = True
        trainer.UseKernelEstimation = True

        Dim svm = trainer.Learn(sample, outs)

        Dim predictResult As Boolean() = svm.Decide(sample)



        Dim zeroOneAnswers As Integer() = predictResult.ToZeroOne()





        ScatterplotBox.Show("实际结果", sample, outs)
        ScatterplotBox.Show("SVM预测结果", sample, zeroOneAnswers).Hold()






    End Sub
End Class