SVM 模型的概率是如何计算的？

机器算法验证 r 支持向量机 libsvm
2022-04-09 19:23:49

我想知道，如何在支持向量机中计算概率。

我使用了 Iris 数据集，这是我对三个“SupportVectorMachine”的决策值（请在下面找到 PMML 以了解支持向量和系数值）。

setosa/versicolor setosa/virginica versicolor/virginica
         1.196152         1.091757            0.6708810

根据“dmg.org”网站中解释的投票机制，我得到的结果是“setosa”

我很困惑如何计算概率值？这些是从 R 获得的概率参数。

model$probA
[1] -3.589058 -3.793546 -3.518305

model$probB
[1] -0.16396052 -0.04387233  0.13178304

来自上述决策函数和概率参数的概率如下。

   setosa versicolor   virginica
0.9795937 0.01161942 0.008786859

更多信息：

内核类型：RBF

输入记录：

Sepal_Length Sepal_Width Petal_Length Petal_Width
         5.1         3.5          1.4         0.2

您能否解释一下，概率是如何计算的？

PMML

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    functionName="classification"
    svmRepresentation="SupportVectors">
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            usageType="active"/>
        <MiningField
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        <MiningField
            name="Petal_Length"
            usageType="active"/>
        <MiningField
            name="Petal_Width"
            usageType="active"/>
        <MiningField
            name="Species"
            usageType="predicted"/>
    </MiningSchema>
    <RadialBasisKernelType
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        <VectorFields
            numberOfFields="4">
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            <FieldRef
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            <FieldRef
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            <FieldRef
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            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-0.563841411833021"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
            <Coefficient
                value="-10"/>
        </Coefficients>
    </SupportVectorMachine>
</SupportVectorMachineModel>
1个回答

您的 SVM 实现很可能基于LibSVM 库。有关如何计算概率的说明，请参阅 LibSVM 的文档（例如，此 FAQ 项目）。

简而言之，概率计算是基于一个单独的过程，它与决策函数没有任何共同之处。甚至有可能决策函数和计算的概率预测不同的类别为获胜者。

PMML 规范不支持 LibSVM 的概率计算过程。因此，您不能将probability输出功能与 SVM 模型一起使用。

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