{"uid":"cap_xSxDdOBdzPjxJtOQygdIa","slug":"meeting-topic-fixed-holdout-learning-curve-26a2c632","name":"Meeting Topic Fixed-Holdout Learning Curve","description":"Meeting topic - Fixed-holdout learning curve: Fixed-holdout learning curve for Meeting topic. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded fixed-holdout learning curve deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-meeting-topic-learning-curve?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["planning","progress","decision","review"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"planning sample document number 0 for this supplied dataset.","actual":"planning"},{"id":"example-0-1","text":"planning sample document number 1 for this supplied dataset.","actual":"planning"},{"id":"example-0-2","text":"planning sample document number 2 for this supplied dataset.","actual":"planning"},{"id":"example-1-0","text":"progress sample document number 0 for this supplied dataset.","actual":"progress"},{"id":"example-1-1","text":"progress sample document number 1 for this supplied dataset.","actual":"progress"},{"id":"example-1-2","text":"progress sample document number 2 for this supplied dataset.","actual":"progress"},{"id":"example-2-0","text":"decision sample document number 0 for this supplied dataset.","actual":"decision"},{"id":"example-2-1","text":"decision sample document number 1 for this supplied dataset.","actual":"decision"},{"id":"example-2-2","text":"decision sample document number 2 for this supplied dataset.","actual":"decision"},{"id":"example-3-0","text":"review sample document number 0 for this supplied dataset.","actual":"review"},{"id":"example-3-1","text":"review sample document number 1 for this supplied dataset.","actual":"review"},{"id":"example-3-2","text":"review sample document number 2 for this supplied dataset.","actual":"review"}],"maxItems":200,"minItems":2}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_VkmwQRs88k2RCMZywrKdQ","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Generates a fixed-holdout learning curve for meeting topic classification (planning/progress/decision/review) using a naive-Bayes baseline on up to 200 labelled text records.","exampleAgentPrompt":"Run a fixed-holdout learning curve on my labelled meeting transcripts — I have about 80 records tagged as planning, progress, decision, or review — and show me how the naive-Bayes baseline accuracy changes as training size grows.","exampleUseCases":[{"title":"Data sufficiency check for meeting classifier","prompt":"I have 150 labelled meeting notes tagged as planning, progress, decision, or review. Can you run a fixed-holdout learning curve on them so I can see whether 150 samples is enough for a naive-Bayes baseline to perform well?"},{"title":"Benchmarking new meeting topic labels","prompt":"We just finished labelling 200 meeting excerpts into four categories — planning, progress, decision, and review. Run a learning curve against a fixed holdout so we can see how accuracy evolves as training data increases."},{"title":"Evaluating small-dataset classifier viability","prompt":"I only have 40 labelled meeting snippets split across planning and decision topics. Can you compute a fixed-holdout learning curve to tell me if a naive-Bayes model is even viable at this sample size?"}],"resultDescription":"Returns a fixed-holdout learning curve showing how naive-Bayes classification accuracy (and related evaluation metrics) changes as the number of training records increases, computed against a held-out portion of the supplied labelled meeting topic records (planning, progress, decision, review).","failureModes":["Fewer than 2 records supplied — minimum input size not met","Records missing required fields (id, text, actual) — validation error","Text exceeds 1000 character limit per record — truncation or rejection","Fewer than one example per class — model cannot learn distinctions","More than 200 records supplied — exceeds maximum input size","Invalid enum value for 'actual' field — only planning/progress/decision/review accepted"],"whenToPreferThis":"Choose this endpoint when you need a quick, cheap ($0.01 USDC) evaluation of how a naive-Bayes baseline learns to classify meeting topics (planning, progress, decision, review) from your own labelled text data, without needing a hosted model or foundation-model training. Ideal for data sufficiency analysis, sanity-checking label quality, or benchmarking small local datasets before committing to larger ML infrastructure.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:47:56.366Z","isFirstParty":false,"canonicalSlug":"meeting-topic-fixed-holdout-learning-curve-26a2c632"}