Unverified50% confidenceFactExact time
When SEED-MAX is combined with F-Test, SEED-MAX is responsible for screening the conditionally dependent feature subset from a global risk perspective, while F-Test performs a second round of trimming from the perspective of statistical significance; the two are complementary, raising the pruning rate from the level achieved by SEED-MAX alone to about 92%.
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50%
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Medium-term (~90 days)
Relevance
10/14/2026
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Valid until: 1/12/2027
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UnverifiedOn the UCR time series classification datasets, the sequential combination of SEED-MAX and F-Test can achieve a pruning rate of about 92% (only 8% of the original random features are retained), while the drop in classification accuracy is almost negligible.67% similarUnverifiedIn the title-abstract screening stage, when researchers provide explicit inclusion and exclusion criteria, model F2 scores can improve by 28.8%61% similarUnverifiedIn the convergence bounds of this paper, the spectral gap determines the effective sample size in the dominant term.60% similarUnverifiedIn the benchmark test, the heuristic peak rule achieved 93.3% overall accuracy, 100.0% impact recall, and 38.4% cadence false positives, requiring manual threshold tuning.59% similar
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