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RQM Fit Coupled Channel Model
x402
RQM Fit Coupled Channel Model is a paid API for AI agents from jobs.rqmtechnologies.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-15).
Fits a bounded structured quaternion ridge regression model to coupled channel features and targets, returning predictions and learned weights.
Price / call$0.005
Success—
StatusUnknown
How this service works
Fit Coupled Channel Model: Fit the bounded structured quaternion ridge model and return predictions and weights. Use when: The caller needs a bounded objective result that can directly gate or feed its next step. Returns: strict JSON summary, checksummed artifact manifest. Boundaries: Bounded deterministic reference processing only; no causal, hardware, operational, performance, classifie...
Output
Returns model predictions (as quaternion-valued outputs per sample) and the learned ridge regression weights for the fitted coupled channel model, structured as a bounded objective result suitable for directly gating or feeding the next agent workflow step.
Example use cases
Multi-channel sensor fusion regression
“I have 4 quaternion-valued sensor channels and 2 output channels — fit a coupled ridge model to my 100 training samples using strict augmentation and regularization of 0.0001, and return the predicted outputs and weights.”
Quaternion signal prediction for control system
“Fit a quaternion ridge regression model with 6 features and 1 output to my 200-sample coupled channel dataset, using selective-j augmentation and regularization 0.00001, so I can gate the next step in my control pipeline based on the bounded prediction.”
Multi-output quaternion model for robotics orientation
“I need to train a bounded quaternion ridge model on 8 coupled feature channels and 3 output channels from my robotics data — 512 samples, strict augmentation, regularization 1e-6 — and get back the predictions to feed into my next workflow stage.”
Technical details
Endpoint
POSThttps://jobs.rqmtechnologies.com/x402/buyer-jobs/fit-coupled-channel-model-v1When to prefer
Choose this endpoint when you need a bounded, structured quaternion ridge regression fit over multi-channel coupled data and require predictions and weights that can directly gate or feed the next step in an automated pipeline. Prefer this over general-purpose ML services when your data is natively quaternion-valued (e.g. orientation, rotation, or complex signal data) and you need a bounded objective with regularization control. Do not use when you need hardware ground truth, causal diagnosis, unbounded streaming inference, or physical simulation.
Side effects
- Feature or target array length mismatch with declared feature_count or output_count
- Array sizes exceed maximum of 512 samples
- feature_count outside range 1–16 or output_count outside range 1–4
- Invalid augmentation enum value (must be 'strict' or 'selective-j')
- Regularization parameter outside valid range (1e-12 to 1000)
- Malformed quaternion samples missing w, x, y, or z fields
- Payment failure or insufficient USDC balance for x402 protocol
- Invalid or missing idempotency_key format
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| request | object | Fit Coupled Channel Model request metadata is discovery-only while execution is disabled. |
| schema_version | — | |
| idempotency_key | string | |
| max_total_price | string |
Tags
x402
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