{"uid":"cap_ZVBYxJmq0HwHPFqnH5s37","slug":"product-category-multiclass-brier-score-912b0200","name":"Product Category Multiclass Brier Score","description":"Product category - Multiclass Brier score: Multiclass Brier score 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 multiclass brier score deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-product-category-brier?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"records":{"type":"array","items":{"type":"object","required":["id","text","actual","predicted","probabilities"],"properties":{"id":{"type":"string","default":"","maxLength":80,"minLength":1},"text":{"type":"string","default":"","maxLength":1000},"actual":{"enum":["apparel","home","electronics","other"],"type":"string"},"predicted":{"enum":["apparel","home","electronics","other"],"type":"string"},"probabilities":{"type":"array","items":{"type":"number","default":0,"maximum":1,"minimum":0},"default":[],"maxItems":4,"minItems":4}},"additionalProperties":false},"default":[{"id":"example-0-0","text":"apparel sample document number 0 for this supplied dataset.","actual":"apparel","predicted":"apparel","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"apparel sample document number 1 for this supplied dataset.","actual":"apparel","predicted":"apparel","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"apparel sample document number 2 for this supplied dataset.","actual":"apparel","predicted":"apparel","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"home sample document number 0 for this supplied dataset.","actual":"home","predicted":"home","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"home sample document number 1 for this supplied dataset.","actual":"home","predicted":"home","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"home sample document number 2 for this supplied dataset.","actual":"home","predicted":"home","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"electronics sample document number 0 for this supplied dataset.","actual":"electronics","predicted":"electronics","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"electronics sample document number 1 for this supplied dataset.","actual":"electronics","predicted":"electronics","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"electronics sample document number 2 for this supplied dataset.","actual":"electronics","predicted":"electronics","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"other sample document number 0 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"other sample document number 1 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"other sample document number 2 for this supplied dataset.","actual":"other","predicted":"other","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]}],"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_eqiUu_9SXWBXq2El9jV4o","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 the multiclass Brier score for product category text classification predictions across apparel, home, electronics, and other classes.","exampleAgentPrompt":"Can you compute the multiclass Brier score for my product category classifier? I have 50 labeled records with text, the actual categories (apparel, home, electronics, or other), predicted categories, and four-element probability vectors for each — I want to know how well-calibrated my probability predictions are.","exampleUseCases":[{"title":"E-commerce classifier calibration check","prompt":"I just trained a naive Bayes classifier to categorize product listings into apparel, home, electronics, or other. I have 120 labeled examples with their actual categories, predicted categories, and the four probability scores for each. Can you run the multiclass Brier score on them so I can see how calibrated my model's confidence is?"},{"title":"A/B comparison of two product classifiers","prompt":"I'm comparing two product category models and want to pick the better-calibrated one. Can you compute the multiclass Brier score for my first model's predictions? I've got 80 records with actual labels (apparel, home, electronics, other), predicted labels, and probability arrays for each."},{"title":"Pre-deployment model quality gate","prompt":"Before I push my product categorization model to production, I need to check its probability calibration on a holdout set of 150 text records across the apparel, home, electronics, and other classes. Can you calculate the multiclass Brier score for me using the actual labels, predicted labels, and class probabilities I have?"}],"resultDescription":"Returns a bounded multiclass Brier score value for the submitted product category predictions, quantifying how well the predicted class probabilities match the true one-hot encoded labels. Lower scores indicate better calibration. The result covers up to 200 labeled records across the four product categories: apparel, home, electronics, and other.","failureModes":["Probability arrays not summing to 1 or containing values outside [0,1] may cause validation errors","Records missing required fields (id, text, actual, predicted, probabilities) will be rejected","Submitting more than 200 records may exceed the allowed limit and result in an error","Invalid actual or predicted category values outside the four allowed enums will fail schema validation","Empty records array returns no meaningful score"],"whenToPreferThis":"Choose this endpoint when you need a fast, inexpensive ($0.01 USDC) evaluation of probability calibration for a text classifier operating over the specific product categories of apparel, home, electronics, and other. It is ideal for lightweight local evaluation without access to a hosted ML platform, or when you want a standardized Brier score deliverable for up to 200 records without setting up your own evaluation pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:16.598Z","isFirstParty":false,"canonicalSlug":"product-category-multiclass-brier-score-912b0200"}