{"uid":"cap_GgSpY1BYRTz2bvy1NKayB","slug":"knowledge-topic-classifier-macro-micro-weighted-scores-954198e7","name":"Knowledge Topic Classifier — Macro, Micro & Weighted Scores","description":"Knowledge topic - Macro micro and weighted scores: Macro micro and weighted scores for Knowledge 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 macro micro and weighted scores deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-knowledge-topic-aggregate-scores?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual","predicted"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["setup","usage","troubleshooting","reference"],"type":"string"},"predicted":{"enum":["setup","usage","troubleshooting","reference"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"setup sample document number 0 for this supplied dataset.","actual":"setup","predicted":"setup"},{"id":"example-0-1","text":"setup sample document number 1 for this supplied dataset.","actual":"setup","predicted":"setup"},{"id":"example-0-2","text":"setup sample document number 2 for this supplied dataset.","actual":"setup","predicted":"setup"},{"id":"example-1-0","text":"usage sample document number 0 for this supplied dataset.","actual":"usage","predicted":"usage"},{"id":"example-1-1","text":"usage sample document number 1 for this supplied dataset.","actual":"usage","predicted":"usage"},{"id":"example-1-2","text":"usage sample document number 2 for this supplied dataset.","actual":"usage","predicted":"usage"},{"id":"example-2-0","text":"troubleshooting sample document number 0 for this supplied dataset.","actual":"troubleshooting","predicted":"troubleshooting"},{"id":"example-2-1","text":"troubleshooting sample document number 1 for this supplied dataset.","actual":"troubleshooting","predicted":"troubleshooting"},{"id":"example-2-2","text":"troubleshooting sample document number 2 for this supplied dataset.","actual":"troubleshooting","predicted":"troubleshooting"},{"id":"example-3-0","text":"reference sample document number 0 for this supplied dataset.","actual":"reference","predicted":"reference"},{"id":"example-3-1","text":"reference sample document number 1 for this supplied dataset.","actual":"reference","predicted":"reference"},{"id":"example-3-2","text":"reference sample document number 2 for this supplied dataset.","actual":"reference","predicted":"reference"}],"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_Yp08gocVhaBSmEWITeZtA","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":"Computes macro, micro, and weighted precision/recall/F1 scores for a knowledge-topic text classifier across four categories: setup, usage, troubleshooting, and reference.","exampleAgentPrompt":"Evaluate my knowledge topic classifier by computing macro, micro, and weighted F1 scores — here are up to 200 labelled records, each with an ID, the text, the actual category (setup, usage, troubleshooting, or reference), and what my model predicted.","exampleUseCases":[{"title":"Documentation classifier quality check","prompt":"I've got 150 labelled knowledge base articles where each one is tagged as setup, usage, troubleshooting, or reference — both the ground truth and what my classifier predicted. Can you compute the macro, micro, and weighted F1 scores so I can see how well it's doing?"},{"title":"Naive Bayes baseline benchmarking","prompt":"I just trained a naive Bayes model to sort support docs into setup, usage, troubleshooting, and reference categories. Here's my test set of 80 records with actual and predicted labels — give me the full macro, micro, and weighted precision, recall, and F1 breakdown."},{"title":"Knowledge topic model regression check","prompt":"Before shipping a new version of our doc classifier, I need to verify it hasn't regressed. Can you take these 200 actual-vs-predicted knowledge topic label pairs and return the macro, micro, and weighted aggregate scores?"}],"resultDescription":"Returns aggregate classification metrics — macro, micro, and weighted precision, recall, and F1 scores — computed over up to 200 supplied records with actual and predicted labels across four knowledge topic categories: setup, usage, troubleshooting, and reference.","failureModes":["Empty records array returns error or degenerate metrics","Records exceeding 200 items may be truncated or rejected","Invalid or missing 'actual'/'predicted' enum values cause validation errors","Imbalanced classes may produce misleading macro averages","Missing required fields (id, text, actual, predicted) cause schema validation failures"],"whenToPreferThis":"Choose this endpoint when you need a quick, cheap ($0.01 USDC) evaluation of a knowledge-topic text classifier that categorizes documents into setup, usage, troubleshooting, and reference — particularly when you already have predicted and actual labels and want macro/micro/weighted aggregate scores without setting up a local evaluation pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:58.883Z","isFirstParty":false,"canonicalSlug":"knowledge-topic-classifier-macro-micro-weighted-scores-954198e7"}