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RETRACTED: Hybrid anomaly detection: Leveraging autoencoder for feature learning and random forest neural network for discriminative classification.

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Title: RETRACTED: Hybrid anomaly detection: Leveraging autoencoder for feature learning and random forest neural network for discriminative classification.
Authors: Maheswari, M.1, maheswam@srmist.edu.in, Anitha, D.1, Sharma, Aditi2, Kaur, Kiranpreet3, Balamurugan, V.4, Garikapati, Bindu5, Dineshkumar, R.6, Karunakaran, P.7
Source: Journal of Intelligent & Fuzzy Systems; 2025 Suppl 1, Vol. 49, p924-937, 14p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191764336
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Intelligent+%26+Fuzzy+Systems%22">Journal of Intelligent & Fuzzy Systems</searchLink>; 2025 Suppl 1, Vol. 49, p924-937, 14p
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      – Type: doi
        Value: 10.3233/JIFS-240028
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      – Code: eng
        Text: English
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        PageCount: 14
        StartPage: 924
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      – TitleFull: RETRACTED: Hybrid anomaly detection: Leveraging autoencoder for feature learning and random forest neural network for discriminative classification.
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              Text: 2025 Suppl 1
              Type: published
              Y: 2025
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              Value: 49
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            – TitleFull: Journal of Intelligent & Fuzzy Systems
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