{"uid":"cap_JE1G1NCErjOpTe8O8W7PD","slug":"release-change-confusion-matrix-22a74ad5","name":"Release Change Confusion Matrix","description":"Release change - Confusion matrix: Confusion matrix for Release change. 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 confusion matrix deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-release-change-confusion?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":["feature","fix","documentation","maintenance"],"type":"string"},"predicted":{"enum":["feature","fix","documentation","maintenance"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"feature sample document number 0 for this supplied dataset.","actual":"feature","predicted":"feature"},{"id":"example-0-1","text":"feature sample document number 1 for this supplied dataset.","actual":"feature","predicted":"feature"},{"id":"example-0-2","text":"feature sample document number 2 for this supplied dataset.","actual":"feature","predicted":"feature"},{"id":"example-1-0","text":"fix sample document number 0 for this supplied dataset.","actual":"fix","predicted":"fix"},{"id":"example-1-1","text":"fix sample document number 1 for this supplied dataset.","actual":"fix","predicted":"fix"},{"id":"example-1-2","text":"fix sample document number 2 for this supplied dataset.","actual":"fix","predicted":"fix"},{"id":"example-2-0","text":"documentation sample document number 0 for this supplied dataset.","actual":"documentation","predicted":"documentation"},{"id":"example-2-1","text":"documentation sample document number 1 for this supplied dataset.","actual":"documentation","predicted":"documentation"},{"id":"example-2-2","text":"documentation sample document number 2 for this supplied dataset.","actual":"documentation","predicted":"documentation"},{"id":"example-3-0","text":"maintenance sample document number 0 for this supplied dataset.","actual":"maintenance","predicted":"maintenance"},{"id":"example-3-1","text":"maintenance sample document number 1 for this supplied dataset.","actual":"maintenance","predicted":"maintenance"},{"id":"example-3-2","text":"maintenance sample document number 2 for this supplied dataset.","actual":"maintenance","predicted":"maintenance"}],"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_iPG5X4XTEXXn01duZK0J_","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 a confusion matrix for release-change text classification across four categories: feature, fix, documentation, and maintenance.","exampleAgentPrompt":"Can you run a confusion matrix on my release change classifier results? I have 50 labelled records where each one has an actual label and predicted label — both drawn from feature, fix, documentation, and maintenance — and I want to see where the model is getting confused.","exampleUseCases":[{"title":"Evaluating a changelog classifier","prompt":"I trained a model to categorize git commit messages into feature, fix, documentation, or maintenance. I have 120 labelled examples with actual and predicted labels — can you compute a confusion matrix so I can see which categories it's mixing up?"},{"title":"Comparing two model predictions on release notes","prompt":"I'm comparing two classifiers on our release notes dataset. Can you run a confusion matrix on the first model's predictions? I have 80 records with actual and predicted labels across feature, fix, documentation, and maintenance."},{"title":"Spotting misclassification patterns before deployment","prompt":"Before we ship our release-change tagging model, I want to sanity-check it. I have 150 labelled records with actual and predicted categories — feature, fix, documentation, or maintenance. Can you compute the confusion matrix so I can see where it's going wrong?"}],"resultDescription":"A bounded confusion matrix deliverable showing how predicted release-change labels (feature, fix, documentation, maintenance) align with actual labels across up to 200 supplied records, including per-class misclassification counts.","failureModes":["Exceeds 200 records limit — request rejected or truncated","Missing required fields (id, text, actual, predicted) on any record — validation error","Invalid enum values for actual or predicted outside the four allowed categories — schema rejection","Empty records array — no matrix can be computed","Text field exceeding 1000 characters per record — field truncation or rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 labelled text records for a release-change classification task and need a quick, low-cost confusion matrix evaluation without standing up your own ML infrastructure. It is ideal for lightweight model evaluation of naive Bayes or small classifiers on software changelog categorization, especially when you need a bounded, pay-per-call evaluation at $0.01 per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:38.594Z","isFirstParty":false,"canonicalSlug":"release-change-confusion-matrix-22a74ad5"}