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Multiclass Log Loss Calculator for Task Type Classification
x402
Multiclass Log Loss Calculator for Task Type Classification is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes multiclass log loss for a task-type text classifier (research/writing/analysis/implementation) given up to 200 labelled records with predicted probabilities.
Price / call$0.01
Success—
StatusUnknown
How this service works
Task type - Multiclass log loss: Multiclass log loss for Task type. 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.
Output
Returns a bounded multiclass log loss value computed from the supplied labelled records, their actual class labels, and the predicted probability vectors across the four task-type categories (research, writing, analysis, implementation). The deliverable is a single log loss metric quantifying classifier quality.
Example use cases
NLP model evaluation before deployment
“I just trained a text classifier that tags documents as research, writing, analysis, or implementation. Can you compute the multiclass log loss over these 80 labelled test records — I have the actual labels, predicted labels, and probability scores for each?”
Comparing classifier calibration quality
“I want to check how well-calibrated my task-type classifier is. Here are 120 records with actual labels and predicted probabilities across all four categories — research, writing, analysis, implementation — can you give me the log loss?”
Rapid baseline model benchmarking
“I built a naive Bayes baseline for classifying task types and want to know the log loss. I have 30 sample records with actual and predicted labels plus the four-class probability distributions — can you run the multiclass log loss calculation?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-task-type-log-loss?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, cheap ($0.01 USDC) multiclass log loss computation for a 4-class task-type text classifier (research/writing/analysis/implementation) without needing a hosted model or foundation-model training. It is ideal for evaluating classifier output from your own model using local datasets of up to 200 records.
Side effects
- Probability vectors that do not sum to 1 or contain values outside [0,1] may cause validation errors
- Supplying fewer than the required fields (id, text, actual, predicted, probabilities) per record will cause schema rejection
- Exceeding the 200-record limit will be rejected
- Probability arrays with fewer or more than 4 elements will fail validation
- Invalid enum values for actual or predicted fields (outside the four allowed classes) will be rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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