{"uid":"cap_T4vKtLW0VpuAz_M0qyT55","slug":"product-category-label-distribution-be041031","name":"Product Category Label Distribution","description":"Product category - Label distribution: Label distribution for Product category. 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-product-category-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":["apparel","home","electronics","other"],"type":"string"}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"apparel sample document number 0 for this supplied dataset.","actual":"apparel"},{"id":"example-0-1","text":"apparel sample document number 1 for this supplied dataset.","actual":"apparel"},{"id":"example-0-2","text":"apparel sample document number 2 for this supplied dataset.","actual":"apparel"},{"id":"example-1-0","text":"home sample document number 0 for this supplied dataset.","actual":"home"},{"id":"example-1-1","text":"home sample document number 1 for this supplied dataset.","actual":"home"},{"id":"example-1-2","text":"home sample document number 2 for this supplied dataset.","actual":"home"},{"id":"example-2-0","text":"electronics sample document number 0 for this supplied dataset.","actual":"electronics"},{"id":"example-2-1","text":"electronics sample document number 1 for this supplied dataset.","actual":"electronics"},{"id":"example-2-2","text":"electronics sample document number 2 for this supplied dataset.","actual":"electronics"},{"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_tVJA8soMT6zqCldW-3c_G","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 for a supplied set of labelled product-category text records (apparel, home, electronics, other)","exampleAgentPrompt":"I have up to 200 labelled product descriptions — each tagged as apparel, home, electronics, or other — can you compute the label distribution so I can see how balanced the dataset is before I train my classifier?","exampleUseCases":[{"title":"Pre-training class imbalance audit","prompt":"Before I train my product classifier, I want to check if my 150 labelled records are evenly spread across apparel, home, electronics, and other — can you compute the label distribution for me?"},{"title":"Dataset quality check for e-commerce catalog","prompt":"I've got a batch of 80 product descriptions all manually tagged — some as apparel, some as home goods, some electronics, and a few as other. Can you tell me how many records fall into each category so I can spot any skew?"},{"title":"Naive-Bayes baseline evaluation prep","prompt":"I'm building a small naive-Bayes product category model and need to know if my 120 training samples are balanced across apparel, home, electronics, and other before I proceed — can you give me the label distribution?"}],"resultDescription":"Returns a label distribution report showing counts and/or proportions of records per product category label (apparel, home, electronics, other) across the up to 200 supplied labelled text records, enabling assessment of class balance.","failureModes":["Fewer than 2 records supplied — minimum item count not met","More than 200 records supplied — exceeds maximum item count","Missing required fields (id, text, actual) on any record","Invalid category value in 'actual' field — must be one of apparel, home, electronics, other","Record ID exceeds 80 characters — validation error","Text field exceeds 1000 characters per record — truncation or rejection","Payment not completed — x402 payment required before response is returned"],"whenToPreferThis":"Choose this endpoint when you have a small set of pre-labelled product text records (up to 200) and need a quick, cheap label distribution summary before building or evaluating a product category classifier. It is ideal for dataset auditing, class-imbalance detection, and naive-Bayes baseline preparation without needing a hosted model or foundation-model API. Prefer it over general-purpose LLM analysis when you want a deterministic, bounded, low-cost computation tied specifically to the four product categories (apparel, home, electronics, other).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T00:53:53.160Z","isFirstParty":false,"canonicalSlug":"product-category-label-distribution-be041031"}