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Delx Weight Normalize
x402
Delx Weight Normalize is a paid API for AI agents from api.delx.ai, paid per call via x402, $0.003/call, status unknown (last checked 2026-09-13).
Normalizes an array of non-negative weights so they sum to 1.0, returning a probability simplex representation suitable for ensemble models and signal preparation.
Price / call$0.003
Success—
StatusUnknown
How this service works
Normalize non-negative weights so they sum to one when possible — call when normalizing non-negative ensemble weights to sum 1. Use on caller-supplied ticks/returns when agents need signal prep without a licensed live market feed (ottoai-class demand, first-party transform). Returns deterministic machine-readable JSON for $0.003 USDC via x402 on Base. Execution is first-party, local-only, stateless, and memory-only with no paid upstream, no input retention, and no claim of live chain tip, web s…
Output
A deterministic JSON object containing the normalized weights array where all values are non-negative and sum to 1.0, suitable for direct use as probability weights, ensemble blending coefficients, or allocation fractions.
Example use cases
Ensemble model blending prep
“I have four model confidence scores — 0.2, 0.8, 1.0, and 0.5 — and I need to turn them into normalized blend weights that sum to 1 before I combine their outputs.”
Portfolio weight normalization
“I've got raw allocation weights of 3, 7, 5, and 10 for four assets — can you normalize those so they sum to 1 so I can use them as portfolio fractions?”
Signal preparation for agent pipeline
“Before I feed these signal strengths [0.1, 0.4, 0.9, 0.6] into my voting layer, I need them normalized to a valid probability distribution — can you do that?”
Technical details
Endpoint
POSThttps://api.delx.ai/api/v1/x402/weight-normalizeWhen to prefer
Choose this endpoint when you need a stateless, deterministic, local-only normalization of non-negative weights with no external dependencies or data retention — ideal for agent pipelines that need simplex projection of ensemble weights, portfolio allocations, or probability distributions without a licensed data feed or heavyweight ML dependency.
Side effects
- All-zero input array — cannot normalize a zero-sum vector, returns error
- Negative values in weights array — violates non-negative constraint, returns validation error
- Empty array — no weights to normalize, returns error
- Non-numeric values in array — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| weights | array | Non-negative weights to normalize so they sum to 1 when possible. |
Output
Schema · Response
{
"type": "json",
"example": {
"sum": 4,
"count": 3,
"valid": true,
"schema": "delx/util-weight-normalize/v1",
"normalized": [
0.25,
0.5,
0.25
]
}
}Tags
x402
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