Unverified50% confidenceFactExact time
The Minner estimator is an improved scheme in the MinHash family that further reduces variance by combining multiple minimum hash values, and typically has lower variance than standard MinHash under the same hash budget.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAfter data deduplication (using locality-sensitive hashing algorithms such as MinHash and SimHash), model convergence speed can improve by 10–20%.66% similarUnverifiedUsing a Haiku-level model for simple classification tasks can reduce the per-call cost to as low as 1/20 of that of a flagship model or even lower.61% similarUnverifiedWAPE is a commonly used evaluation metric in demand forecasting, calculated as the sum of absolute errors across all samples divided by the sum of actual values and then multiplied by 100%; compared with MAPE it is more robust for low-sales or zero-sales items, and a WAPE below 30% is generally considered a good level.56% similarUnverified轻量版模型单次推理的算力消耗往往只有旗舰版本的十分之一甚至更低55% similarUnverifiedDue to their smaller parameter count, lightweight models are generally weaker than flagship models in coverage of rare APIs or niche libraries.54% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1026615API
curl https://kongchang.com/api/v1/knowledge/claims/1026615MCP
get_claim(id=1026615)