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The paper uses a k-nearest neighbor classifier (k-NN) as a test platform to compare the performance of several supervised distances derived from these representations on prediction tasks.
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10/9/2026
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UnverifiedK-fold cross-validation divides the data evenly into K folds, taking one fold in turn as the validation set and the remaining K-1 folds as the training set, and finally averaging the results of K runs.70% similarUnverifiedEvidently 内置了 KS 检验、卡方检验、PSI 等多种统计检验方法来量化漂移程度，并根据特征数据类型自动选择合适的检验方法69% similarUnverifiedIn k-fold cross-validation, each fold produces a set of performance metric values, providing paired observation samples for the Wilcoxon signed-rank test.68% similarUnverifiedResearch settings typically allow multiple samplings and problem-type-specific prompt design, so researchers distinguish between the pass@k metric and the single-attempt pass rate.66% similarUnverifiedMethods for overfitting benchmarks include mixing evaluation data into training corpora, indirect web-crawl contamination, instruction-style fine-tuning, and training models to recognize evaluation scenarios.65% similar
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