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Project Status Multiclass Log Loss Calculator
x402
Project Status Multiclass Log Loss Calculator 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 metric for project status classification models over up to 200 labeled text records
Price / call$0.01
Success—
StatusUnknown
How this service works
Project status - Multiclass log loss: Multiclass log loss for Project status. 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 across the submitted labeled records, reflecting how well the model's predicted probability distributions align with the actual project status labels (planned, active, blocked, complete). Lower values indicate better-calibrated predictions.
Example use cases
Evaluating a sprint status classifier
“I've trained a model to classify tickets as planned, active, blocked, or complete and I want to know its log loss. I have 50 labeled examples each with the ticket text, the true status, my model's predicted status, and the 4-class probability outputs — can you run the multiclass log loss calculation on them?”
Comparing two project models side by side
“I have two versions of my project status classifier and want to compare their log loss scores. Here are 80 records with the actual labels and the predicted probabilities from Model A — can you compute the multiclass log loss so I can benchmark it against Model B?”
Checking probability calibration on blocked projects
“My classifier keeps mislabeling blocked projects and I want to see how bad the log loss is specifically across my 30 blocked-status records. Each record has the text description, the actual status 'blocked', my model's predicted label, and the four probability scores — can you compute the log loss for this set?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-project-status-log-loss?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, cheap ($0.01) multiclass log loss evaluation for a project status classifier with exactly four classes (planned, active, blocked, complete) and up to 200 labeled records. It is ideal for lightweight model evaluation without needing a hosted model or foundation-model infrastructure. Prefer it over general-purpose ML evaluation APIs when your domain is specifically project lifecycle status classification and you want a single bounded metric deliverable.
Side effects
- Records array exceeds 200 items — request rejected
- Probability array does not contain exactly 4 elements per record — validation error
- Probability values outside [0,1] range — schema validation failure
- Missing required fields (id, text, actual, predicted, probabilities) in any record — error
- Payment of 0.01 USDC not provided or rejected — 402 payment required
- Malformed JSON body — 400 bad request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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