Feature selection approach using ensemble learning for network anomaly detection (Unknown)
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- Article (Journal) / Electronic Resource
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Title:Feature selection approach using ensemble learning for network anomaly detection
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Published in:
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Publication date:2020
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ISSN:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:Unknown
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Keywords:feature selection , decision trees , data mining , pattern classification , security of data , support vector machines , bayes methods , feature extraction , regression analysis , random forests , machine learning algorithms , primary individual selection methods , recursive feature elimination , absolute selection , shrinkage operator , discard redundant features , individual methods , equalise individual feature sets , equalised individual feature sets , quorum techniques , network anomaly detection , random forest , quorum feature , feature selection approach , ensemble learning , Computational linguistics. Natural language processing , P98-98.5 , Computer software , QA76.75-76.765
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