{"uid":"cap_2nd5ld-2Q70JGs7Evm8b-","slug":"subscription-request-multiclass-log-loss-calculator-09f3687f","name":"Subscription Request Multiclass Log Loss Calculator","description":"Subscription request - Multiclass log loss: Multiclass log loss for Subscription request. 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 log loss deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-subscription-request-log-loss?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":["upgrade","downgrade","cancel","renew"],"type":"string"},"predicted":{"enum":["upgrade","downgrade","cancel","renew"],"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":"upgrade sample document number 0 for this supplied dataset.","actual":"upgrade","predicted":"upgrade","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-1","text":"upgrade sample document number 1 for this supplied dataset.","actual":"upgrade","predicted":"upgrade","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-0-2","text":"upgrade sample document number 2 for this supplied dataset.","actual":"upgrade","predicted":"upgrade","probabilities":[0.8,0.06666666666666667,0.06666666666666667,0.06666666666666667]},{"id":"example-1-0","text":"downgrade sample document number 0 for this supplied dataset.","actual":"downgrade","predicted":"downgrade","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-1","text":"downgrade sample document number 1 for this supplied dataset.","actual":"downgrade","predicted":"downgrade","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-1-2","text":"downgrade sample document number 2 for this supplied dataset.","actual":"downgrade","predicted":"downgrade","probabilities":[0.06666666666666667,0.8,0.06666666666666667,0.06666666666666667]},{"id":"example-2-0","text":"cancel sample document number 0 for this supplied dataset.","actual":"cancel","predicted":"cancel","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-1","text":"cancel sample document number 1 for this supplied dataset.","actual":"cancel","predicted":"cancel","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-2-2","text":"cancel sample document number 2 for this supplied dataset.","actual":"cancel","predicted":"cancel","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"renew sample document number 0 for this supplied dataset.","actual":"renew","predicted":"renew","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"renew sample document number 1 for this supplied dataset.","actual":"renew","predicted":"renew","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"renew sample document number 2 for this supplied dataset.","actual":"renew","predicted":"renew","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_raAo3pzloWPkTfzLdgkK7","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 multiclass log loss for subscription request text classification models across upgrade, downgrade, cancel, and renew classes","exampleAgentPrompt":"Can you calculate the multiclass log loss for my subscription request classifier? I have 50 labeled records where each one has the actual label (upgrade, downgrade, cancel, or renew), my model's predicted label, and the four class probabilities — for example, record 'sub-001' with text 'I want to move to the Pro tier', actual label 'upgrade', predicted 'upgrade', and probabilities [0.85, 0.05, 0.05, 0.05].","exampleUseCases":[{"title":"Subscription churn model evaluation","prompt":"I've trained a classifier to predict whether customers will upgrade, downgrade, cancel, or renew their subscription, and I need to measure its log loss on 120 validation records — each record has the customer message text, the true outcome label, my model's top predicted label, and the four probability scores. Can you run the multiclass log loss calculation for me?"},{"title":"A/B testing classifier comparison","prompt":"I'm comparing two subscription intent models and want to know which has lower log loss on the same 80 labeled examples — the records include the support ticket text, actual subscription action taken (upgrade, downgrade, cancel, or renew), and both models' probability outputs. Can you compute the log loss for the first model's predictions?"},{"title":"Pre-deployment model quality check","prompt":"Before pushing my subscription request classifier to production, I need to verify its multiclass log loss on 60 hold-out records with actual and predicted labels across upgrade, downgrade, cancel, and renew — each record also has the four class probabilities. Can you evaluate that for me and give me the log loss score?"}],"resultDescription":"Returns a bounded multiclass log loss deliverable computed from the supplied labeled records, including the aggregate cross-entropy log loss score across the four subscription request classes (upgrade, downgrade, cancel, renew), based on predicted probability vectors versus actual labels.","failureModes":["Probability arrays not summing to 1.0 may cause computation errors","Records with fewer or more than 4 probability values will be rejected due to minItems/maxItems constraint","Invalid or missing actual/predicted enum values (must be upgrade, downgrade, cancel, or renew) will fail validation","Exceeding 200 records per call will be rejected","Empty records array returns no meaningful output","Record IDs exceeding 80 characters or missing entirely cause schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need a fast, cheap ($0.01 USDC) multiclass log loss evaluation specifically for subscription request text classification with the four fixed classes (upgrade, downgrade, cancel, renew) and up to 200 records. It is ideal for lightweight model evaluation pipelines, quick benchmarking, or validation checks where you already have predicted probabilities and ground truth labels and do not need hosted model training or inference.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:43:36.292Z","isFirstParty":false,"canonicalSlug":"subscription-request-multiclass-log-loss-calculator-09f3687f"}