Matches in SemOpenAlex for { <https://semopenalex.org/work/W2892493072> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W2892493072 endingPage "68" @default.
- W2892493072 startingPage "47" @default.
- W2892493072 abstract "FL is a technique that models the behavior of data from a subset of attributes only. It also shows the correlation between detection performance and traffic model quality efficiently (Palmieri et al., Concurrency Comput Pract Exp 26(5):1113–1129, 2014). However, feature extraction and feature selection are different. Feature extraction algorithms derive new features from the original features to (i) reduce the cost of feature measurement, (ii) increase classifier efficiency, and (iii) improve classification accuracy, whereas feature selection algorithms select no more than m features from a total of M input features, where m is smaller than M. Thus, the newly generated features were merely selected from the original features without any transformation. However, their goal is to derive or select a characteristic feature vector with a lower dimensionality which is used for the classification task. One advantage of deep learning models is processing underlying data from the input which suits for FL tasks. Therefore, we discuss this critical role of deep learning in IDS as Deep Feature Extraction and Selection (D-FES) and deep learning for clustering." @default.
- W2892493072 created "2018-10-05" @default.
- W2892493072 creator A5039785089 @default.
- W2892493072 creator A5045098894 @default.
- W2892493072 creator A5069543375 @default.
- W2892493072 date "2018-01-01" @default.
- W2892493072 modified "2023-10-16" @default.
- W2892493072 title "Deep Feature Learning" @default.
- W2892493072 cites W1966156248 @default.
- W2892493072 cites W1974089633 @default.
- W2892493072 cites W1985987493 @default.
- W2892493072 cites W2017337590 @default.
- W2892493072 cites W2028070713 @default.
- W2892493072 cites W2051812123 @default.
- W2892493072 cites W2130613448 @default.
- W2892493072 cites W2133990480 @default.
- W2892493072 cites W2143426320 @default.
- W2892493072 cites W2512496029 @default.
- W2892493072 cites W2532890539 @default.
- W2892493072 cites W2566616303 @default.
- W2892493072 cites W2602255610 @default.
- W2892493072 cites W2763978449 @default.
- W2892493072 cites W2809178492 @default.
- W2892493072 cites W3123463689 @default.
- W2892493072 cites W4231109964 @default.
- W2892493072 cites W4246198815 @default.
- W2892493072 doi "https://doi.org/10.1007/978-981-13-1444-5_6" @default.
- W2892493072 hasPublicationYear "2018" @default.
- W2892493072 type Work @default.
- W2892493072 sameAs 2892493072 @default.
- W2892493072 citedByCount "2" @default.
- W2892493072 countsByYear W28924930722020 @default.
- W2892493072 countsByYear W28924930722023 @default.
- W2892493072 crossrefType "book-chapter" @default.
- W2892493072 hasAuthorship W2892493072A5039785089 @default.
- W2892493072 hasAuthorship W2892493072A5045098894 @default.
- W2892493072 hasAuthorship W2892493072A5069543375 @default.
- W2892493072 hasConcept C111030470 @default.
- W2892493072 hasConcept C119857082 @default.
- W2892493072 hasConcept C124101348 @default.
- W2892493072 hasConcept C148483581 @default.
- W2892493072 hasConcept C153180895 @default.
- W2892493072 hasConcept C154945302 @default.
- W2892493072 hasConcept C41008148 @default.
- W2892493072 hasConcept C52622490 @default.
- W2892493072 hasConcept C70518039 @default.
- W2892493072 hasConcept C73555534 @default.
- W2892493072 hasConcept C95623464 @default.
- W2892493072 hasConceptScore W2892493072C111030470 @default.
- W2892493072 hasConceptScore W2892493072C119857082 @default.
- W2892493072 hasConceptScore W2892493072C124101348 @default.
- W2892493072 hasConceptScore W2892493072C148483581 @default.
- W2892493072 hasConceptScore W2892493072C153180895 @default.
- W2892493072 hasConceptScore W2892493072C154945302 @default.
- W2892493072 hasConceptScore W2892493072C41008148 @default.
- W2892493072 hasConceptScore W2892493072C52622490 @default.
- W2892493072 hasConceptScore W2892493072C70518039 @default.
- W2892493072 hasConceptScore W2892493072C73555534 @default.
- W2892493072 hasConceptScore W2892493072C95623464 @default.
- W2892493072 hasLocation W28924930721 @default.
- W2892493072 hasOpenAccess W2892493072 @default.
- W2892493072 hasPrimaryLocation W28924930721 @default.
- W2892493072 hasRelatedWork W1552543208 @default.
- W2892493072 hasRelatedWork W1641615907 @default.
- W2892493072 hasRelatedWork W1995622179 @default.
- W2892493072 hasRelatedWork W20047544 @default.
- W2892493072 hasRelatedWork W2074396517 @default.
- W2892493072 hasRelatedWork W2093956241 @default.
- W2892493072 hasRelatedWork W2166963679 @default.
- W2892493072 hasRelatedWork W2354420595 @default.
- W2892493072 hasRelatedWork W3089231081 @default.
- W2892493072 hasRelatedWork W2187269125 @default.
- W2892493072 isParatext "false" @default.
- W2892493072 isRetracted "false" @default.
- W2892493072 magId "2892493072" @default.
- W2892493072 workType "book-chapter" @default.