{"uid":"cap_niyognjH23pavWajsC7Db","slug":"training-question-prediction-error-records-analyzer-bbef84ab","name":"Training Question Prediction Error Records Analyzer","description":"Training question - Prediction error records: Prediction error records for Training question. 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 prediction error records deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-ml-training-question-errors?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":["concept","procedure","example","assessment"],"type":"string"},"predicted":{"enum":["concept","procedure","example","assessment"],"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":"concept sample document number 0 for this supplied 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dataset.","actual":"example","predicted":"example","probabilities":[0.06666666666666667,0.06666666666666667,0.8,0.06666666666666667]},{"id":"example-3-0","text":"assessment sample document number 0 for this supplied dataset.","actual":"assessment","predicted":"assessment","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-1","text":"assessment sample document number 1 for this supplied dataset.","actual":"assessment","predicted":"assessment","probabilities":[0.06666666666666667,0.06666666666666667,0.06666666666666667,0.8]},{"id":"example-3-2","text":"assessment sample document number 2 for this supplied 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prediction error records for a naive-Bayes text classifier trained on training question categories (concept, procedure, example, assessment) given up to 200 labelled records with actual vs predicted labels and class probabilities.","exampleAgentPrompt":"Analyze prediction errors for my training question classifier — I have 12 labelled records with actual and predicted labels across concept, procedure, example, and assessment categories, plus the 4-class probability scores for each. Can you compute the prediction error records and tell me where the model went wrong?","exampleUseCases":[{"title":"Audit misclassified educational question types","prompt":"I have 50 labelled training questions where each one has an actual label (concept, procedure, example, or assessment) and what my naive-Bayes classifier predicted, along with the 4 class probabilities. Can you run prediction error records on them so I can see exactly which records the model got wrong?"},{"title":"Debug classifier errors before retraining","prompt":"Before I retrain my question categorization model, I want to see the prediction error records for my current model on 30 validation examples — each has an id, the question text, the true category, what was predicted, and the probability distribution across concept, procedure, example, and assessment. Can you generate that error report?"},{"title":"Compare model predictions to human labels","prompt":"I've got 80 human-labelled training questions with model predictions and probability scores across the four classes: concept, procedure, example, and assessment. Please compute prediction error records so I can compare where the model diverges from the human labels."}],"resultDescription":"A bounded deliverable containing prediction error records: details of which supplied labelled text records were misclassified, including the record id, text, actual label, predicted label, and probability distribution — enabling analysis of classifier weaknesses across the concept, procedure, example, and assessment categories.","failureModes":["More than 200 records supplied — input exceeds maximum batch size","Missing required fields (id, text, actual, predicted, probabilities) on any record — validation error","Probabilities array does not have exactly 4 elements or values outside [0,1] — schema validation failure","Invalid enum value for actual or predicted (must be concept, procedure, example, or assessment) — rejected","Payment not processed or insufficient USDC balance — 402 payment required error"],"whenToPreferThis":"Use this endpoint when you need a lightweight, low-cost ($0.01) prediction error analysis for up to 200 labelled text records classified into the four training question categories (concept, procedure, example, assessment). Ideal for local model evaluation workflows, debugging naive-Bayes classifiers, or auditing misclassifications without needing a hosted ML model or foundation model. Not suitable for large-scale datasets, training new models, or categories outside the four supported labels.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:54:40.383Z","isFirstParty":false,"canonicalSlug":"training-question-prediction-error-records-analyzer-bbef84ab"}