.net随笔-vb.net Accord.Net机器学习之SVM分类

线性核分类

 Imports Accord.ControlsImports Accord.IOImports Accord.MathImports Accord.Statistics.Distributions.UnivariateImports Accord.MachineLearning.VectorMachines.LearningImports Accord.StatisticsImports SystemPublic 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.ClickNaiveBayes()End SubPrivate 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 SubEnd 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 SystemPublic 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.ClickNaiveBayes()End SubPrivate 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 = Truetrainer.UseKernelEstimation = TrueDim 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

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