TrainTextContentDetector

TrainTextContentDetector[{text1{span1class1,},}]

根据所给的样例训练 ContentDetectorFunction[].

更多信息和选项

范例

打开所有单元关闭所有单元

基本范例  (1)

训练一个简单的实体检测器:

对新的文本应用该检测器:

范围  (1)

训练检测器,识别多个类别:

对新的文本应用该检测器:

查询检测到的文本片段的特定属性:

选项  (4)

PerformanceGoal  (1)

PerformanceGoal"Quality" 强调结果的质量:

PerformanceGoal"Speed" 强调计算的速度:

ProgressReporting  (1)

默认情况下,在动态面板中报告进度:

ProgressReportingFalse 禁止显示进度面板:

TimeGoal  (1)

训练时间可能受多种因素影响,如样例和类别的数量:

TimeGoal 指定额定的训练时间:

ValidationSet  (1)

默认情况下,不对检测器进行验证. 用 ValidationSet 提供验证数据:

Wolfram Research (2021),TrainTextContentDetector,Wolfram 语言函数,https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

文本

Wolfram Research (2021),TrainTextContentDetector,Wolfram 语言函数,https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

CMS

Wolfram 语言. 2021. "TrainTextContentDetector." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

APA

Wolfram 语言. (2021). TrainTextContentDetector. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/TrainTextContentDetector.html 年

BibTeX

@misc{reference.wolfram_2024_traintextcontentdetector, author="Wolfram Research", title="{TrainTextContentDetector}", year="2021", howpublished="\url{https://reference.wolfram.com/language/ref/TrainTextContentDetector.html}", note=[Accessed: 18-November-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_traintextcontentdetector, organization={Wolfram Research}, title={TrainTextContentDetector}, year={2021}, url={https://reference.wolfram.com/language/ref/TrainTextContentDetector.html}, note=[Accessed: 18-November-2024 ]}