Matches in SemOpenAlex for { <https://semopenalex.org/work/W3170397312> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W3170397312 abstract "Feature selection is extremely important in machine learning and data mining. Typical two-objective feature selection methods aim to minimize the number of features and maximize classification performance. However, they overlook the fact that there may be multiple subsets with similar information content for a given cardinality. The paper presents a many-objective feature selection approach to address this problem. Firstly, we establish a five-objective optimization model, which consists of classification accuracy, the number of features, feature relevance, feature redundancy, and feature complementarity. Therefore, the proposed model can enlarge the search space with more Pareto solutions. Secondly, we propose a wrapper structure for many-objective feature selection, which integrates a learning algorithm. Thirdly, in order to reduce the computional overhead, we propose a filter structure, which separates the learning algorithm. For implementation, we adopt NSGA-III multi-objective evolutionary algorithm and extreme learning machine. The experiments on mainstream datasets confirm the superiority of the proposed method." @default.
- W3170397312 created "2021-06-22" @default.
- W3170397312 creator A5006794114 @default.
- W3170397312 creator A5023106937 @default.
- W3170397312 creator A5042400671 @default.
- W3170397312 creator A5050607325 @default.
- W3170397312 date "2021-05-05" @default.
- W3170397312 modified "2023-09-27" @default.
- W3170397312 title "A Novel Feature Selection with Many-Objective Optimization and Learning Mechanism" @default.
- W3170397312 cites W1502251266 @default.
- W3170397312 cites W2015743664 @default.
- W3170397312 cites W2048541604 @default.
- W3170397312 cites W2050399271 @default.
- W3170397312 cites W2154053567 @default.
- W3170397312 cites W2397044210 @default.
- W3170397312 cites W2767105247 @default.
- W3170397312 cites W2791315675 @default.
- W3170397312 cites W2884719158 @default.
- W3170397312 cites W2906625258 @default.
- W3170397312 doi "https://doi.org/10.1109/cscwd49262.2021.9437707" @default.
- W3170397312 hasPublicationYear "2021" @default.
- W3170397312 type Work @default.
- W3170397312 sameAs 3170397312 @default.
- W3170397312 citedByCount "0" @default.
- W3170397312 crossrefType "proceedings-article" @default.
- W3170397312 hasAuthorship W3170397312A5006794114 @default.
- W3170397312 hasAuthorship W3170397312A5023106937 @default.
- W3170397312 hasAuthorship W3170397312A5042400671 @default.
- W3170397312 hasAuthorship W3170397312A5050607325 @default.
- W3170397312 hasConcept C111919701 @default.
- W3170397312 hasConcept C119857082 @default.
- W3170397312 hasConcept C124101348 @default.
- W3170397312 hasConcept C126255220 @default.
- W3170397312 hasConcept C137635306 @default.
- W3170397312 hasConcept C138885662 @default.
- W3170397312 hasConcept C148483581 @default.
- W3170397312 hasConcept C152124472 @default.
- W3170397312 hasConcept C154945302 @default.
- W3170397312 hasConcept C16811321 @default.
- W3170397312 hasConcept C2776401178 @default.
- W3170397312 hasConcept C33923547 @default.
- W3170397312 hasConcept C41008148 @default.
- W3170397312 hasConcept C41895202 @default.
- W3170397312 hasConcept C59404180 @default.
- W3170397312 hasConcept C68781425 @default.
- W3170397312 hasConceptScore W3170397312C111919701 @default.
- W3170397312 hasConceptScore W3170397312C119857082 @default.
- W3170397312 hasConceptScore W3170397312C124101348 @default.
- W3170397312 hasConceptScore W3170397312C126255220 @default.
- W3170397312 hasConceptScore W3170397312C137635306 @default.
- W3170397312 hasConceptScore W3170397312C138885662 @default.
- W3170397312 hasConceptScore W3170397312C148483581 @default.
- W3170397312 hasConceptScore W3170397312C152124472 @default.
- W3170397312 hasConceptScore W3170397312C154945302 @default.
- W3170397312 hasConceptScore W3170397312C16811321 @default.
- W3170397312 hasConceptScore W3170397312C2776401178 @default.
- W3170397312 hasConceptScore W3170397312C33923547 @default.
- W3170397312 hasConceptScore W3170397312C41008148 @default.
- W3170397312 hasConceptScore W3170397312C41895202 @default.
- W3170397312 hasConceptScore W3170397312C59404180 @default.
- W3170397312 hasConceptScore W3170397312C68781425 @default.
- W3170397312 hasFunder F4320321001 @default.
- W3170397312 hasFunder F4320335777 @default.
- W3170397312 hasLocation W31703973121 @default.
- W3170397312 hasOpenAccess W3170397312 @default.
- W3170397312 hasPrimaryLocation W31703973121 @default.
- W3170397312 hasRelatedWork W1520730836 @default.
- W3170397312 hasRelatedWork W2163070219 @default.
- W3170397312 hasRelatedWork W2188393372 @default.
- W3170397312 hasRelatedWork W2277968882 @default.
- W3170397312 hasRelatedWork W2286904880 @default.
- W3170397312 hasRelatedWork W2296226123 @default.
- W3170397312 hasRelatedWork W2392236103 @default.
- W3170397312 hasRelatedWork W3012439478 @default.
- W3170397312 hasRelatedWork W3149253111 @default.
- W3170397312 hasRelatedWork W4295514622 @default.
- W3170397312 isParatext "false" @default.
- W3170397312 isRetracted "false" @default.
- W3170397312 magId "3170397312" @default.
- W3170397312 workType "article" @default.