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May, 2025
基于偏好嵌入的异常检测方法PIF
PIF: Anomaly detection via preference embedding
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Filippo Leveni, Luca Magri, Giacomo Boracchi, Cesare Alippi
TL;DR
本文针对结构模式下的异常检测问题，提出了一种新颖的异常检测方法PIF，该方法结合了自适应隔离方法的优势和偏好嵌入的灵活性。实验结果表明，PIF在合成和真实数据集上优于现有的异常检测技术，证明PI-Forest在测量任意距离和隔离偏好空间中的点方面更具优势。
Abstract
We address the problem of detecting anomalies with respect to structured patterns. To this end, we conceive a novel
Anomaly Detection
method called PIF, that combines the advantages of adaptive
Isolation Methods
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