Labelset-Based (Classification Method) - Revision history

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2026-01-30T17:05:17Z

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			<blockquote>{{#lst:Glossary\|Labelset-Based}}</blockquote>

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	~~'''WIP'''~~		[[File:Asset 22@4x.png]]
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	~~This article is a work-in-progress or created as a placeholder for testing purposes~~. ~~This article is subject to change and/~~or ~~expansion~~. ~~It may be incomplete, inaccurate,~~ or ~~stop abruptly~~.		You may download the ZIP(s) below and upload it into your own Grooper environment (version 2025). The first contains one or more '''Batches''' of sample documents. The second contains one or more '''Projects''' with resources used in examples throughout this article.
			* [[Media:2025 Wiki Labeset-Based-Classification Batches.zip]]
	~~This tag will be removed upon draft completion~~.		* [[Media:2025 Wiki Labelset-Based-Classification Project.zip]]
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	~~<blockquote>{{#lst:Glossary\|Labelset-Based}}</blockquote>~~

	== Introduction ==		== Introduction ==

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 == How to configure Labelset-Based Classification ==
 '''Step-by-step'''
 # Navigate to the Content Model in your Project.
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 #* Review candidates and final assignment in the Classification Tester.
 #* If needed, refine Label Sets (add alternate label versions, clarify headers/footers, mark volatile labels) and retest.
 <div style="position: relative; box-sizing: content-box; max-height: 80vh; max-height: 80svh; width: 100%; aspect-ratio: 1.78; padding: 40px 0 40px 0;"><iframe src="https://app.supademo.com/embed/cmky973y600ugrf0jvced5j10?embed_v=2&utm_source=embed" loading="lazy" title="01 Labeset-Based Classification - Basic Configuration" allow="clipboard-write" frameborder="0" webkitallowfullscreen="true" mozallowfullscreen="true" allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
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 * Leverage first-page labels when documents are highly identifiable on page 1.
 * Use "Page Scope - Classification" to speed up classification on large documents.
 == Properties overview ==

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2026-01-30T14:23:47Z

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	* Each Document Type should have a defined '''Label Set''' with labels for its expected fields, sections, and tables configured.		* Each Document Type should have a defined '''Label Set''' with labels for its expected fields, sections, and tables configured.
	* Recognized text on the documents must be available for classification.		* Recognized text on the documents must be available for classification.

			== How to configure Labelset-Based Classification ==
			'''Step-by-step'''
			# Navigate to the Content Model in your Project.
			# In the Content Model properties, set "Classification Method" to '''Labelset-Based'''.
			# Apply a [[Labeling Behavior]] on the Content Model or Content Category to enable Labelsets.
			# Click over to the '''Labels''' tab.
			# Define one or more labels for each key [[Data Field]], [[Data Section]], and/or [[Data Table]].
			#* Each Data Field, Data Section, or Data Table must have a Labelset-aware Value Extractor set on each node for Labels to be collected.
			# Test your configuration:
			#* Use a Classify [[Batch Process]] step to test and evaluate results.
			#* Review candidates and final assignment in the Classification Tester.
			#* If needed, refine Label Sets (add alternate label versions, clarify headers/footers, mark volatile labels) and retest.


			<div style="position: relative; box-sizing: content-box; max-height: 80vh; max-height: 80svh; width: 100%; aspect-ratio: 1.78; padding: 40px 0 40px 0;"><iframe src="https://app.supademo.com/embed/cmky973y600ugrf0jvced5j10?embed_v=2&utm_source=embed" loading="lazy" title="01 Labeset-Based Classification - Basic Configuration" allow="clipboard-write" frameborder="0" webkitallowfullscreen="true" mozallowfullscreen="true" allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>


			'''Tips'''
			* Start with essential labels (headers, table columns) that reliably identify the type.
			* Include alternate label versions for common variations (e.g., “Invoice #”, “Inv No.”).
			* Leverage first-page labels when documents are highly identifiable on page 1.
			* Use "Page Scope - Classification" to speed up classification on large documents.

			== Properties overview ==
			The following properties are specific to the Labelset-Based classification method. Property names are shown as they appear in the UI.

			'''Labelset-Based'''
			* "Prescan Threshold"
			** '''Definition:''' The percentage of labelset words that must be present in the document to trigger full labelset extraction.
			** '''Remarks:'''
			*** 0% (default): All Label Sets are fully executed for every document, ensuring maximum thoroughness.
			*** Greater than 0%: Only Label Sets where at least the specified percentage of words are found in the document are executed, improving performance by skipping unlikely matches.
			*** Example: If set to 0.5 (50%), a Label Set is fully executed only if at least half of its words are found in the document text.
			*** Adjust to balance speed vs. thoroughness for your solution.
			** '''Purpose / use case:''' Use higher values to speed up classification in solutions with many document types or large batches, and lower values when completeness is more important than speed.

			'''Related settings affecting Labelset-Based Classification'''
			* [[Content Model]] – "Page Scope - Classification"
			** '''Definition:''' Limits the number of pages analyzed during classification.
			** '''Purpose / use case:''' Speeds up OCR and classification by focusing on the most relevant pages (e.g., first page).
			* Licensing – [[Classification Volume]]
			** '''Definition:''' Tracks the quantity of classifications performed (“documents”).
			** '''Purpose / use case:''' Ensure available classification volume covers your processing needs.

			== Testing and troubleshooting ==
			'''If no type is selected:'''
			* Verify that the parent object has a '''Labeling Behavior'''.
			* Confirm each candidate [[Document Type]] has a non-empty '''Label Set'''.
			* Check OCR text availability; run or configure OCR earlier in the [[Batch Process]].
			* Lower "Prescan Threshold" to avoid skipping valid types.

			'''If classification is slow:'''
			* Increase "Prescan Threshold" to skip unlikely types.
			* Reduce "Page Scope - Classification" to analyze fewer pages.

			'''If classification selects the wrong type:'''
			* Strengthen distinctive labels in each Label Set.
			* Add alternate versions for common label variations.
			* Review first-page labels if the first page is most indicative.
			* Use classification rules on [[Document Type]]s (such as positive/negative extractors or page count constraints) to reinforce selection.

			== Keyboard and commands ==
			* To quickly test, use the '''Classify''' command on selected [[Batch Folder]]s.
			* Use standard shortcuts for running steps, e.g., <kbd>Alt</kbd> + <kbd>F5</kbd> in appropriate testing contexts (varies by tester UI; see local documentation).
			* For separation scenarios, verify first-page labels and related behaviors before running the [[Separate]] activity.

			== Summary ==
			Labelset-Based Classification provides accurate typing for semi-structured document sets by matching known labels per [[Document Type]]. With minimal setup—a Labeling Behavior and Label Sets—it enables rapid onboarding, clear diagnostics, and strong performance, especially when tuned with "Prescan Threshold" and "Page Scope - Classification".

Rpatton at 15:53, 28 January 2026

2026-01-28T15:53:08Z

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			== Introduction ==
			'''Labelset-Based Classification''' is a [[Classification]] method that uses the configured [[Label Sets]] for each [[Document Type]] to determine the best match. It analyzes a document's text for the presence of known labels (Data Fields, field headers, table column names, section titles, etc.) and scores each candidate type based on label coverage and quality. The highest-scoring Document Type is selected.

			Use Labelset-Based Classification when your documents are semi-structured: they consistently use similar text labels to identify data, but layouts may vary by vendor, version, or template.

			Compared to training-based or rules-only methods, Labelset-Based Classification focuses on label presence rather than learned features, making it fast to onboard new Document Types by creating or updating Label Sets.

			'''How it works (brief):'''
			# For each candidate Document Type in the selected [[Content Model]] scope, the method loads its '''Label Set'''.
			# It quickly prescans for label words (optional), then executes the label readers to find matches.
			# It computes a score based on the number of matched labels and their quality, applies classification rules, and selects the best-scoring Document Type.

			== When to use ==
			'''Ideal use cases'''
			* Semi-structured sets where consistent labels (e.g., “Invoice Number”, “Policy ID”, “Patient Name”) appear even if formatting differs.
			* Solutions needing rapid onboarding of new templates by authoring Label Sets rather than retraining models.
			* Mixed layouts where label presence and quality reliably indicate Document Type.

			'''Real-world example'''
			* Accounts payable: supplier invoices vary widely in layout, but common labels (such as “Invoice Number”, “Invoice Date”, “Total”, “Line Items”) are present. Labelset-Based Classification correctly identifies invoice types using those labels without extensive training data.

			'''Prerequisites'''
			* A Content Model with one or more child Document Types in scope.
			* A [[Labeling Behavior]] configured on the parent Content Model or [[Content Category]] so Label Sets are available.
			* Each Document Type should have a defined '''Label Set''' with labels for its expected fields, sections, and tables configured.
			* Recognized text on the documents must be available for classification.

Rpatton: Removed redirect to Labeling Behavior (Behavior)#About Labelset-Based Classification

2026-01-28T15:07:52Z

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			'''WIP'''
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			This article is a work-in-progress or created as a placeholder for testing purposes. This article is subject to change and/or expansion. It may be incomplete, inaccurate, or stop abruptly.

			This tag will be removed upon draft completion.
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			<blockquote>{{#lst:Glossary\|Labelset-Based}}</blockquote>

Randallkinard: Changed redirect target from Labeling Behavior#About Labelset-Based Classification to Labeling Behavior (Behavior)#About Labelset-Based Classification

2024-04-17T19:30:29Z

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Dgreenwood: Changed redirect target from Labeling Behavior - 2021#About Labelset-Based Classification to Labeling Behavior#About Labelset-Based Classification

2024-01-02T14:40:23Z

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2023-09-20T22:34:34Z

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