{"uid":"cap_lMrdwAkn1UVHgJTKNlVOE","slug":"return-reason-label-distribution-ff28ea37","name":"Return Reason Label Distribution","description":"Return reason - Label distribution: Label distribution 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 label distribution deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-label-balance?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_g7pMhIURfRYwlXzbO3I3K","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 label distribution statistics across up to 200 labelled return-reason text records, categorized as damaged, wrong_item, unwanted, or other.","exampleAgentPrompt":"Can you check the label balance in my return reason dataset? I have about 50 labelled records — some marked 'damaged', some 'wrong_item', some 'unwanted', and some 'other' — and I want to see the distribution across those categories.","exampleUseCases":[{"title":"Pre-training dataset audit","prompt":"Before I train my return reason classifier, can you check whether my 150 labelled records are balanced across the damaged, wrong_item, unwanted, and other categories? Here are the records with their IDs, text, and actual labels."},{"title":"Class imbalance detection for ML pipeline","prompt":"I'm building a returns triage model and I think my training data might be skewed heavily toward 'damaged'. Can you compute the label distribution across all four return reason classes for my 80 labelled examples so I can see if I need to oversample?"},{"title":"QA check on labelling batch","prompt":"My team just finished labelling a batch of 120 customer return comments as damaged, wrong_item, unwanted, or other. Can you show me the breakdown of how many fall into each category so I can QA the labelling effort?"}],"resultDescription":"A bounded label distribution deliverable showing the count and/or proportion of records assigned to each return reason class (damaged, wrong_item, unwanted, other) across the supplied dataset of up to 200 labelled records.","failureModes":["Fewer than 2 records supplied — minimum item count not met","More than 200 records supplied — exceeds maximum item count","Record missing required 'id', 'text', or 'actual' field — validation error","Invalid 'actual' enum value not in [damaged, wrong_item, unwanted, other] — schema rejection","Empty or overly long text field exceeding 1000 characters — field-level validation failure","Payment not processed — x402 payment required before response is returned"],"whenToPreferThis":"Choose this endpoint when you need a quick, cheap ($0.01 USDC) statistical summary of label balance in a small labelled dataset (up to 200 records) for the specific four-class return reason taxonomy (damaged, wrong_item, unwanted, other). It is ideal for pre-training dataset audits, class imbalance detection, and QA checks on labelling batches without needing a hosted model or full ML pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:35.463Z","isFirstParty":false,"canonicalSlug":"return-reason-label-distribution-ff28ea37"}