{"uid":"cap_QoVzAvrGsZQoMbhQPhAXH","slug":"return-reason-classifier-supplied-group-evaluation-b22a98bc","name":"Return Reason Classifier – Supplied-Group Evaluation","description":"Return reason - Supplied-group evaluation: Supplied-group evaluation 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 supplied-group evaluation deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-return-reason-group-evaluation?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual","predicted","group"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"group":{"type":"string","default":"","maxLength":80},"actual":{"enum":["damaged","wrong_item","unwanted","other"],"type":"string"},"predicted":{"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.","group":"a","actual":"damaged","predicted":"damaged"},{"id":"example-0-1","text":"damaged sample document number 1 for this supplied dataset.","group":"b","actual":"damaged","predicted":"damaged"},{"id":"example-0-2","text":"damaged sample document number 2 for this supplied dataset.","group":"a","actual":"damaged","predicted":"damaged"},{"id":"example-1-0","text":"wrong_item sample document number 0 for this supplied dataset.","group":"a","actual":"wrong_item","predicted":"wrong_item"},{"id":"example-1-1","text":"wrong_item sample document number 1 for this supplied dataset.","group":"b","actual":"wrong_item","predicted":"wrong_item"},{"id":"example-1-2","text":"wrong_item sample document number 2 for this supplied dataset.","group":"a","actual":"wrong_item","predicted":"wrong_item"},{"id":"example-2-0","text":"unwanted sample document number 0 for this supplied dataset.","group":"a","actual":"unwanted","predicted":"unwanted"},{"id":"example-2-1","text":"unwanted sample document number 1 for this supplied dataset.","group":"b","actual":"unwanted","predicted":"unwanted"},{"id":"example-2-2","text":"unwanted sample document number 2 for this supplied dataset.","group":"a","actual":"unwanted","predicted":"unwanted"},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","group":"a","actual":"other","predicted":"other"},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","group":"b","actual":"other","predicted":"other"},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","group":"a","actual":"other","predicted":"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_ykhwAsUVVyqkuWQHVLNUu","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":"Evaluates a supplied set of labeled return-reason text records (up to 200) broken down by group, computing per-group classification metrics against predicted and actual labels.","exampleAgentPrompt":"Run a group-level evaluation of my return reason classifier — I have 120 labeled records with actual and predicted labels (damaged, wrong_item, unwanted, or other) split across two groups, 'warehouse-A' and 'warehouse-B'. Can you score each group's classification performance?","exampleUseCases":[{"title":"Regional classifier audit for returns","prompt":"I have 180 return records with actual and predicted labels across three regional groups — north, south, and east. Each record has the return text and both the true label and my model's prediction. Run a group evaluation so I can see which region has the worst classification accuracy for return reasons like damaged or wrong_item."},{"title":"A/B test of two labeling strategies","prompt":"I ran two labeling strategies — call them group 'rule-based' and group 'ml-model' — on 100 return reason texts. I have the actual labels and each strategy's predicted label. Can you evaluate how each group performs across categories like unwanted and damaged?"},{"title":"Product category return model benchmarking","prompt":"Before I deploy my return reason classifier to production, I want to benchmark it across product categories: electronics, apparel, and home. I have 150 labeled examples with actual and predicted return reasons (damaged, wrong_item, unwanted, other). Please run a group evaluation broken down by those categories."}],"resultDescription":"A structured report containing per-group classification metrics for the return reason categories (damaged, wrong_item, unwanted, other), including accuracy, per-class precision/recall, and potentially a confusion summary — derived from the supplied labeled records using local naive-Bayes baselines and evaluation tooling. No hosted model training occurs.","failureModes":["More than 200 records supplied — batch will be rejected or truncated","Missing required fields (id, text, actual, predicted, group) on any record — validation error","Invalid enum value for actual or predicted (must be one of: damaged, wrong_item, unwanted, other) — schema rejection","Empty records array — returns no meaningful metrics","Imbalanced groups with very few samples may yield unreliable metrics"],"whenToPreferThis":"Choose this endpoint when you need to evaluate a return-reason text classifier at a group/segment level using your own labeled dataset (up to 200 records), and you want per-group metrics rather than a single aggregate score. It is ideal for auditing classifier fairness across regions, product categories, or labeling strategies. It does not train or host a model — use it for evaluation and benchmarking only.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:29.747Z","isFirstParty":false,"canonicalSlug":"return-reason-classifier-supplied-group-evaluation-b22a98bc"}