Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/16642
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cholakoska, Ana | en_US |
dc.contributor.author | Shushlevska, Martina | en_US |
dc.contributor.author | Todorov, Zdravko | en_US |
dc.contributor.author | Efnusheva, Danijela | en_US |
dc.date.accessioned | 2022-02-21T11:00:50Z | - |
dc.date.available | 2022-02-21T11:00:50Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/16642 | - |
dc.language.iso | en | en_US |
dc.publisher | Springer International Publishing | en_US |
dc.title | Analysis of Machine Learning Classification Techniques for Anomaly Detection with NSL-KDD Data Set | en_US |
dc.type | Book chapter | en_US |
dc.relation.conference | Lecture Notes in Networks and Systems | en_US |
dc.identifier.doi | 10.1007/978-3-030-90321-3_21 | - |
dc.identifier.url | https://link.springer.com/content/pdf/10.1007/978-3-030-90321-3_21 | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
Appears in Collections: | Faculty of Electrical Engineering and Information Technologies: Book Chapters |
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