Advances in frequent itemset mining implementations 论文

2004ACM SIGKDD Explorations Newsletter引用 238
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Data Mining Algorithms and ApplicationsRough Sets and Fuzzy LogicImbalanced Data Classification Techniques
Imbalanced Data Classification TechniquesData Mining Algorithms and ApplicationsRough Sets and Fuzzy Logic
相关技术:Imbalanced Data Classification TechniquesData Mining Algorithms and Applications
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article Advances in frequent itemset mining implementations: report on FIMI'03 Share on Authors: Bart Goethals University of Helsinki, Finland University of Helsinki, FinlandView Profile , Mohammed J. Zaki Rensselaer Polytechnic Institute, Troy, New York Rensselaer Polytechnic Institute, Troy, New YorkView Profile Authors Info & Claims ACM SIGKDD Explorations NewsletterVolume 6Issue 1June 2004 pp 109–117https://doi.org/10.1145/1007730.1007744Online:01 June 2004Publication History 159citation759DownloadsMetricsTotal Citations159Total Downloads759Last 12 Months15Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

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Mohammed J. Zaki

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Bart Goethals

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Imbalanced Data Classification TechniquesData Mining Algorithms and Applications

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