ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest

ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest

In this study, we present a novel model called ADA-NAF (Anomaly Detection Autoencoder with the Neural Attention Forest) for semi-supervised anomaly detection that uniquely integrates the Neural Attention Forest (NAF) architecture which has been developed to combine a random forest classifier with a...

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Bibliographic Details
Main Authors: Andrey Ageev, Andrei Konstantinov, Lev Utkin
Format: Article
Language:English
Published: Russian Academy of Sciences, St. Petersburg Federal Research Center 2025-01-01
Series:Информатика и автоматизация
Subjects:
anomaly detection
random forest
attention mechanism
neural attention forest
Online Access:https://ia.spcras.ru/index.php/sp/article/view/16598
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