{"uid":"cap_rTm2f-T5D26rHl9I0Mt64","slug":"return-reason-grouped-dataset-split-c971dad8","name":"Return Reason - Grouped Dataset Split","description":"Return reason - Grouped dataset split: Grouped dataset split 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 grouped dataset split deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-dataset-split?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_i7Bmq9JkXWP-BLu4ORMsr","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":"Splits up to 200 labelled return-reason text records into a grouped train/test dataset partition for local naive-Bayes baseline evaluation.","exampleAgentPrompt":"Split these 12 labelled return-reason records — covering damaged, wrong_item, unwanted, and other categories — into a grouped dataset partition so I can run a naive-Bayes baseline evaluation locally.","exampleUseCases":[{"title":"E-commerce return classifier baseline","prompt":"I have 80 labelled customer return comments tagged as damaged, wrong_item, unwanted, or other — can you split them into a grouped dataset partition so I can benchmark a naive-Bayes classifier on them?"},{"title":"QA team dataset evaluation prep","prompt":"Our QA team collected 150 return-reason text samples with actual labels. Split them into grouped train/test sets so we can evaluate our local classification model's performance."},{"title":"Small-scale ML experiment setup","prompt":"I'm running a quick ML experiment on return reasons and have 40 short text records labelled damaged or unwanted. Give me a grouped dataset split I can use to test a simple baseline model."}],"resultDescription":"A grouped dataset split deliverable containing the supplied labelled text records (up to 200) partitioned by return reason category (damaged, wrong_item, unwanted, other), suitable for local naive-Bayes baseline training and evaluation. No hosted model or foundation-model training is performed.","failureModes":["Fewer than 2 records supplied — minimum item count not met","More than 200 records supplied — exceeds maxItems limit","Invalid or missing 'actual' enum value (must be one of: damaged, wrong_item, unwanted, other)","Record text exceeds 1000 characters — truncation or rejection","Missing required fields (id, text, actual) on any record — validation error","Payment failure via x402 protocol — endpoint returns 402 with payment details"],"whenToPreferThis":"Choose this endpoint when you have a small labelled dataset of return-reason text (up to 200 records) and need a quick, cheap grouped train/test split for local naive-Bayes baseline evaluation. Ideal for e-commerce or logistics teams running lightweight ML experiments without requiring a hosted or foundation model. Not suitable for large-scale datasets, deep learning pipelines, or scenarios requiring a trained inference model as output.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:56:58.045Z","isFirstParty":false,"canonicalSlug":"return-reason-grouped-dataset-split-c971dad8"}