{"uid":"cap_wll7I4hAni3qOG-OabFHe","slug":"return-reason-classifier-fixed-holdout-learning-curve-bf705bcd","name":"Return Reason Classifier – Fixed-Holdout Learning Curve","description":"Return reason - Fixed-holdout learning curve: Fixed-holdout learning curve for Return reason. 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-return-reason-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":["damaged","wrong_item","unwanted","other"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"damaged sample document number 0 for this supplied dataset.","actual":"damaged"},{"id":"example-0-1","text":"damaged sample document number 1 for this supplied dataset.","actual":"damaged"},{"id":"example-0-2","text":"damaged sample document number 2 for this supplied dataset.","actual":"damaged"},{"id":"example-1-0","text":"wrong_item sample document number 0 for this supplied dataset.","actual":"wrong_item"},{"id":"example-1-1","text":"wrong_item sample document number 1 for this supplied dataset.","actual":"wrong_item"},{"id":"example-1-2","text":"wrong_item sample document number 2 for this supplied dataset.","actual":"wrong_item"},{"id":"example-2-0","text":"unwanted sample document number 0 for this supplied dataset.","actual":"unwanted"},{"id":"example-2-1","text":"unwanted sample document number 1 for this supplied dataset.","actual":"unwanted"},{"id":"example-2-2","text":"unwanted sample document number 2 for this supplied dataset.","actual":"unwanted"},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other"},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other"},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other"}],"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_-cE236udOSAOAkTaN-OZf","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 a naive-Bayes return-reason text classifier using up to 200 user-supplied labelled records, without any hosted or foundation-model training.","exampleAgentPrompt":"Run a fixed-holdout learning curve for my return reason classifier using these 150 labelled customer messages — each tagged as damaged, wrong_item, unwanted, or other — and tell me how the naive-Bayes baseline accuracy changes as training size increases.","exampleUseCases":[{"title":"Labelled data sufficiency check for returns","prompt":"I have 120 labelled customer return messages tagged as damaged, wrong_item, unwanted, or other — can you run a fixed-holdout learning curve so I can see if collecting more labels would meaningfully improve classification accuracy?"},{"title":"Naive-Bayes baseline benchmark for returns team","prompt":"Our returns team tagged 200 customer complaint texts with one of four reasons: damaged, wrong_item, unwanted, or other. Run a learning curve analysis with a fixed holdout so we can benchmark how a simple naive-Bayes model performs across different training sizes."},{"title":"Early-stage dataset quality assessment","prompt":"We only have about 40 labelled return reason examples split across damaged, wrong_item, unwanted, and other — can you compute a fixed-holdout learning curve to see whether the data quality and volume are good enough to train a basic classifier?"}],"resultDescription":"A fixed-holdout learning curve deliverable showing how a naive-Bayes text classifier's performance metrics (e.g. accuracy) vary as the training set size increases, evaluated against a held-out portion of the supplied labelled records. Includes local baseline evaluation results without any hosted model or foundation-model training.","failureModes":["Fewer than 2 records supplied — minimum input violation","Records missing required fields (id, text, actual) — schema validation error","More than 200 records submitted — maxItems constraint exceeded","Invalid 'actual' enum value (not one of: damaged, wrong_item, unwanted, other) — rejected","Insufficient class diversity in records may produce degenerate learning curves","Payment failure via x402 protocol — endpoint returns 402 status"],"whenToPreferThis":"Choose this endpoint when you have a small labelled dataset (up to 200 records) of customer return reason texts and want a quick, low-cost learning curve analysis using a naive-Bayes baseline — particularly when you don't need a hosted model or foundation-model fine-tuning, and just want to understand how classifier performance scales with training data size for the four standard return reason categories.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T00:54:23.904Z","isFirstParty":false,"canonicalSlug":"return-reason-classifier-fixed-holdout-learning-curve-bf705bcd"}