Term · Topic
Principal Component Analysis (PCA)
Principal component analysis is a statistical dimensionality reduction technique that converts correlated variables into uncorrelated principal components, enabling enterprises to simplify high-dimensional datasets, reduce computational load, and support more stable modeling and analytics in machine learning and business intelligence workflows.
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Vendors describe the same technology in different words. This record pins down what "PCA" means and ties it to the companies and coverage that use it, so an agent compares like with like.
One definition
A plain definition plus how it's used, what it's often confused with and why it matters.
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Related terms in the same glossary, so an agent can widen or narrow a search the way the market does.
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MCP
curl -X POST https://mcp.decisioninsights.ai/api/mcp-public \
-H "content-type: application/json" \
-H "accept: application/json, text/event-stream" \
-d '{"id":1,"jsonrpc":"2.0","method":"tools/call","params":{"arguments":{"slug":"principal-component-analysis-pca"},"name":"di_get_term"}}'REST
GET https://api.decisioninsights.ai/api/public/v1/glossary/f956af31-2f96-4297-832b-f3c35a7390f2CLI
di get-glossary --slug principal-component-analysis-pcaJSON-LD
The schema.org markup this page publishes for search engines and AI agents, exactly as they read it.
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]Is this your company? Get structured data for your own pages
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How an agent can rely on this definition
What the record lets an agent check before it uses the term in an answer.
| The check | What the record shows | Where it is in the data |
|---|---|---|
| It's a known term | One entry, with its abbreviation and type (topic) | name, alternateName |
| It sits in a glossary | Linked to Dimensionality Reduction, OLAP Cube, Predictive Analytics Dashboard, Feature Extraction | inDefinedTermSet |
View the raw record (JSON-LD)
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