WOLFRAM

Wolfram 语言与系统参考资料中心

IndeterminateThreshold

是 Classify、Predict 及相关函数的选项，指定低于什么概率或概率密度结果应被认为是不确定的.

更多信息
Details and Options Details and Options
范例  
基本范例  
范围  
属性和关系  
参见
历史
按以下格式引用：

IndeterminateThreshold

IndeterminateThreshold

是 Classify、Predict 及相关函数的选项，指定低于什么概率或概率密度结果应被认为是不确定的.

更多信息

  • 当 IndeterminateThresholdp0 时，如果预测值的概率或概率密度小于 p0，将返回 Indeterminate.

范例

打开所有单元 关闭所有单元

基本范例  (2)

训练逻辑分类器：

Wolfram Language code: c = Classify[{1 -> "a", 2 -> "b", 3 -> "a", 4 -> "b", 5 -> "b"}, Method -> "LogisticRegression"]

确定新样例最可能的类别：

Wolfram Language code: c[2.5]

获取实际的类别概率：

Wolfram Language code: c[2.5, "Probabilities"]

为分类的类别概率设置 IndeterminateThreshold：

Wolfram Language code: c[2.5, IndeterminateThreshold -> 0.9]

训练线性预测器：

Wolfram Language code: p = Predict[{1 -> 0.24, 2 -> 0.31, 3 -> 0.5, 4 -> 0.6}, Method -> "LinearRegression"]

获取给定样例的概率分布：

Wolfram Language code: p[2.5, "Distribution"]

预测最可能的值：

Wolfram Language code: p[2.5]

为预测的概率密度设置 IndeterminateThreshold：

Wolfram Language code: p[2.5, IndeterminateThreshold -> 20]

范围  (8)

设置分类器训练时的默认概率阈值：

Wolfram Language code: c = Classify[{1 -> "a", 2 -> "b", 3 -> "a", 4 -> "b", 5 -> "b"}, Method -> "LogisticRegression", IndeterminateThreshold -> 0.9]

获取分类结果：

Wolfram Language code: c[2.5]

从 ClassifierFunction 中提取 IndeterminateThreshold：

Wolfram Language code: Information[ClassifierFunction[Association["ExampleNumber" -> 5, "ClassNumber" -> 2, "Input" -> Association["Preprocessor" -> MachineLearning`MLProcessor["ToMLDataset", Association["Input" -> Association["f1" -> Association["Type" -> "Numerical"]], ... te" -> DateObject[{2026, 1, 22, 17, 43, 46.655315`8.42147610258836}, "Instant", "Gregorian", 1.], "ProcessorCount" -> 4, "ProcessorType" -> "x86-64", "OperatingSystem" -> "MacOSX", "SystemWordLength" -> 64, "Evaluations" -> {}]]], IndeterminateThreshold]

修改 IndeterminateThreshold 的值，获取 ClassifierFunction：

Wolfram Language code: Classify[ClassifierFunction[Association["ExampleNumber" -> 5, "ClassNumber" -> 2, "Input" -> Association["Preprocessor" -> MachineLearning`MLProcessor["ToMLDataset", Association["Input" -> Association["f1" -> Association["Type" -> "Numerical"]], ... te" -> DateObject[{2026, 1, 22, 17, 43, 46.655315`8.42147610258836}, "Instant", "Gregorian", 1.], "ProcessorCount" -> 4, "ProcessorType" -> "x86-64", "OperatingSystem" -> "MacOSX", "SystemWordLength" -> 64, "Evaluations" -> {}]]], IndeterminateThreshold -> 0.3]

为内置分类器设置 IndeterminateThreshold 的值：

Wolfram Language code: Classify["FacebookTopic", "I love carrots!"]
Wolfram Language code: Classify["FacebookTopic", "I love carrots!", IndeterminateThreshold -> 0.9]

设置预测器训练时的概率阈值：

Wolfram Language code: p = Predict[{1 -> 0.24, 2 -> 0.31, 3 -> 0.5, 4 -> 0.6}, Method -> "LinearRegression", IndeterminateThreshold -> 20]

获取预测结果：

Wolfram Language code: p[2.5]

从 PredictorFunction 中提取当前 IndeterminateThreshold 的值：

Wolfram Language code: Information[PredictorFunction[Association["ExampleNumber" -> 4, "Input" -> Association["Preprocessor" -> MachineLearning`MLProcessor["ToMLDataset", Association["Input" -> Association["f1" -> Association["Type" -> "Numerical"]], "Output" -> As ... e" -> DateObject[{2026, 1, 22, 17, 9, 11.084835`7.7973042190975175}, "Instant", "Gregorian", 1.], "ProcessorCount" -> 4, "ProcessorType" -> "x86-64", "OperatingSystem" -> "MacOSX", "SystemWordLength" -> 64, "Evaluations" -> {}]]], IndeterminateThreshold]

修改 IndeterminateThreshold 的值，获取 PredictorFunction：

Wolfram Language code: Predict[PredictorFunction[Association["ExampleNumber" -> 4, "Input" -> Association["Preprocessor" -> MachineLearning`MLProcessor["ToMLDataset", Association["Input" -> Association["f1" -> Association["Type" -> "Numerical"]], "Output" -> As ... e" -> DateObject[{2026, 1, 22, 17, 9, 11.084835`7.7973042190975175}, "Instant", "Gregorian", 1.], "ProcessorCount" -> 4, "ProcessorType" -> "x86-64", "OperatingSystem" -> "MacOSX", "SystemWordLength" -> 64, "Evaluations" -> {}]]], IndeterminateThreshold -> 0.3]

修改内置分类器中 IndeterminateThreshold 的值：

Wolfram Language code: Predict["NameAge"]["John"]
Wolfram Language code: Predict["NameAge", "John", IndeterminateThreshold -> 0.5]

属性和关系  (1)

训练线性预测器：

Wolfram Language code: p = Predict[{1 -> 0.24, 2 -> 0.31, 3 -> 0.5, 4 -> 0.6}, Method -> "LinearRegression"]

可视化给定范例的概率密度：

Wolfram Language code: Plot[PDF[p[2.5, "Distribution"]][x], {x, 0, 1}, PlotRange -> All]

对于此例，预测值及其对应的概率密度如下：

Wolfram Language code: p[2.5]
Wolfram Language code: pdf[p[2.5]]

如果阈值高于该概率密度，则得不到预测值：

Wolfram Language code: p[2.5, IndeterminateThreshold -> 20]
Wolfram Research (2014)，IndeterminateThreshold，Wolfram 语言函数，https://reference.wolfram.com/language/ref/IndeterminateThreshold.html.

文本

Wolfram Research (2014)，IndeterminateThreshold，Wolfram 语言函数，https://reference.wolfram.com/language/ref/IndeterminateThreshold.html.

CMS

Wolfram 语言. 2014. "IndeterminateThreshold." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/IndeterminateThreshold.html.

APA

Wolfram 语言. (2014). IndeterminateThreshold. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/IndeterminateThreshold.html 年

BibTeX

@misc{reference.wolfram_2026_indeterminatethreshold, author="Wolfram Research", title="{IndeterminateThreshold}", year="2014", howpublished="\url{https://reference.wolfram.com/language/ref/IndeterminateThreshold.html}", note=[Accessed: 02-November-2026]}

BibLaTeX

@online{reference.wolfram_2026_indeterminatethreshold, organization={Wolfram Research}, title={IndeterminateThreshold}, year={2014}, url={https://reference.wolfram.com/language/ref/IndeterminateThreshold.html}, note=[Accessed: 02-November-2026]}