Unverified50% confidenceBenchmarkExact time
In the benchmark, Random Forest (100 trees) achieved 100.0% overall accuracy, 0.19 ms CPU latency, and 0.0% step-frequency false alarms, but required GridSearchCV tuning.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/12/2026
First Seen
Valid until: 1/10/2027
Sources
Related Entities
Related Claims
UnverifiedIn a benchmark of 30 held-out test windows, TabPFN achieved 100.0% overall accuracy, 100.0% shock recall, 0.33 ms CPU latency, 0.0% step-frequency false alarms, and required no training or tuning.71% similarUnverifiedOn the AG News dataset (n=48), using a forest acquisition approach with four questions achieved an accuracy of 0.729, outperforming static gain ranking at 0.667 and random ordering at 0.583.70% similarUnverifiedIn the fact-updating task, the success rate of the embedding retrieval method fluctuated between 0.30 and 0.95, with a maximum gap of 0.45 across different random seeds.66% similarUnverifiedRandom Forest achieved an F1 score of 0.97 on the IEEE-30 system and reached 0.86 on the IEEE-14 system.64% similarUnverifiedIn zero-shot testing on an unseen grid of 6,470 buses (approximately 40% larger than any grid in training), the cost error increases by about 10%, but the model can still rank scenarios by cost with near-perfect accuracy.64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1007776API
curl https://kongchang.com/api/v1/knowledge/claims/1007776MCP
get_claim(id=1007776)