{"uid":"cap_4BVHQa2iQedJQAc-1hJRU","slug":"sentiment-top-k-label-coverage-d42681bc","name":"Sentiment Top-k Label Coverage","description":"Sentiment - Top-k label coverage: Top-k label coverage for Sentiment. 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 top-k label coverage deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-top-k?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"k":{"type":"integer","default":2,"maximum":3,"minimum":1},"records":{"type":"array","items":{"type":"object","required":["id","text","actual","predicted","probabilities"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["positive","neutral","negative"],"type":"string"},"predicted":{"enum":["positive","neutral","negative"],"type":"string"},"probabilities":{"type":"array","items":{"type":"number","default":0,"maximum":1,"minimum":0},"default":[],"maxItems":3,"minItems":3}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"positive sample document number 0 for this supplied dataset.","actual":"positive","predicted":"positive","probabilities":[0.8,0.1,0.1]},{"id":"example-0-1","text":"positive sample document number 1 for this supplied dataset.","actual":"positive","predicted":"positive","probabilities":[0.8,0.1,0.1]},{"id":"example-0-2","text":"positive sample document number 2 for this supplied dataset.","actual":"positive","predicted":"positive","probabilities":[0.8,0.1,0.1]},{"id":"example-1-0","text":"neutral sample document number 0 for this supplied dataset.","actual":"neutral","predicted":"neutral","probabilities":[0.1,0.8,0.1]},{"id":"example-1-1","text":"neutral sample document number 1 for this supplied dataset.","actual":"neutral","predicted":"neutral","probabilities":[0.1,0.8,0.1]},{"id":"example-1-2","text":"neutral sample document number 2 for this supplied dataset.","actual":"neutral","predicted":"neutral","probabilities":[0.1,0.8,0.1]},{"id":"example-2-0","text":"negative sample document number 0 for this supplied dataset.","actual":"negative","predicted":"negative","probabilities":[0.1,0.1,0.8]},{"id":"example-2-1","text":"negative sample document number 1 for this supplied dataset.","actual":"negative","predicted":"negative","probabilities":[0.1,0.1,0.8]},{"id":"example-2-2","text":"negative sample document number 2 for this supplied dataset.","actual":"negative","predicted":"negative","probabilities":[0.1,0.1,0.8]}],"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_XDpEpBKmTu1AwtycRAWgJ","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 top-k label coverage metrics for sentiment classification results across up to 200 labelled text records","exampleAgentPrompt":"Calculate the top-2 label coverage for my sentiment classifier — I have 50 labelled records each with actual labels (positive, neutral, or negative), predicted labels, and a 3-element probability vector. Can you run the top-k coverage evaluation and tell me the score?","exampleUseCases":[{"title":"Sentiment model evaluation on review data","prompt":"I trained a sentiment classifier on customer reviews and want to know if the correct label (positive, neutral, or negative) shows up in the top 2 predicted labels. I have 100 labelled records with probabilities — can you compute the top-2 label coverage?"},{"title":"Comparing classifier quality before deployment","prompt":"Before I deploy my new sentiment model, I need to check top-k label coverage with k=1 on 80 test samples — each has an actual label, a predicted label, and 3 probability scores. Can you run that evaluation for me?"},{"title":"Validating naive-Bayes sentiment baseline","prompt":"I built a naive-Bayes sentiment baseline and want to evaluate its top-3 label coverage on 200 text records — all labelled positive, neutral, or negative with probability arrays. Can you compute the coverage metric?"}],"resultDescription":"Returns a bounded top-k label coverage deliverable: a numeric coverage score indicating the fraction of records where the true sentiment label (positive, neutral, or negative) falls within the top k predicted labels, based on the supplied probability vectors.","failureModes":["More than 200 records supplied — exceeds the per-call limit","Probability arrays not summing to 1 or having fewer/more than 3 elements","Invalid or missing label values outside the positive/neutral/negative enum","k value outside the allowed range of 1–3","Malformed record IDs exceeding 80 characters or missing required fields","Payment failure via x402 protocol"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) computation of top-k label coverage for a 3-class sentiment classification task (positive/neutral/negative) on up to 200 records. Ideal for quick evaluation of local classifiers or naive-Bayes baselines without needing a hosted model or foundation model. Best suited for small dataset evaluation runs where you already have predicted labels and probability scores.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:53:28.085Z","isFirstParty":false,"canonicalSlug":"sentiment-top-k-label-coverage-d42681bc"}