TrainTextContentDetector

TrainTextContentDetector[{text1{span1class1,},}]

trains a ContentDetectorFunction[] based on the examples given.

Details

Examples

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Basic Examples  (1)

Train a simple entity detector:

Apply the detector on a new text:

Scope  (1)

Train a detector to identify multiple classes:

Apply the detector on new texts:

Ask for particular properties about detected snippets of text:

Options  (4)

PerformanceGoal  (1)

Use PerformanceGoal"Quality" to emphasize the quality of the result:

Use PerformanceGoal"Speed" to emphasize the speed of computation:

ProgressReporting  (1)

By default, progress is reported in a panel:

Use ProgressReportingFalse to avoid displaying the progress panel:

TimeGoal  (1)

The training time can be influenced by several factors, such as the number of examples and classes:

Use TimeGoal to specify a target time for the training:

ValidationSet  (1)

By default, no validation is performed on the detector. Use ValidationSet to provide validation data:

Wolfram Research (2021), TrainTextContentDetector, Wolfram Language function, https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

Text

Wolfram Research (2021), TrainTextContentDetector, Wolfram Language function, https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

CMS

Wolfram Language. 2021. "TrainTextContentDetector." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/TrainTextContentDetector.html.

APA

Wolfram Language. (2021). TrainTextContentDetector. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/TrainTextContentDetector.html

BibTeX

@misc{reference.wolfram_2022_traintextcontentdetector, author="Wolfram Research", title="{TrainTextContentDetector}", year="2021", howpublished="\url{https://reference.wolfram.com/language/ref/TrainTextContentDetector.html}", note=[Accessed: 05-July-2022 ]}

BibLaTeX

@online{reference.wolfram_2022_traintextcontentdetector, organization={Wolfram Research}, title={TrainTextContentDetector}, year={2021}, url={https://reference.wolfram.com/language/ref/TrainTextContentDetector.html}, note=[Accessed: 05-July-2022 ]}