FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3134815509> ?p ?o ?g. }

• W3134815509 endingPage "145" @default.
• W3134815509 startingPage "125" @default.
• W3134815509 abstract "In this article, we consider the semi-supervised data stream classification problems. Most of the semi-supervised learning algorithms suffer from a proper selection metric to select from the newly-labeled data points through the training procedure. These approaches mainly employ the probability estimation of the underlying base learners to their predictions as a selection metric, which is not optimal in many cases. Handling different kinds of concept drifts is another issue in data streams. Considering these issues, we propose a novel Semi-Supervised Ensemble algorithm using a Performance-Based Selection metric to data streams, named SSE-PBS. The proposed selection metric is based on a pseudo-accuracy and energy regularization factor. We show that SSE-PBS improves classification performance and handles different kinds of concept drifts. The proposed algorithm can also employ any kind of incremental base learners. In the experiments, we report the results of two base learners on synthetic and real-world datasets. The experiments show that SSE-PBS significantly improves the classification performance of the used underlying base learners. Furthermore, we compare the results to the state-of-the-art supervised and semi-supervised approaches in data streams. The results further show that SSE-PBS outperforms the other methods when there is a small portion of labeled instances." @default.
• W3134815509 created "2021-03-15" @default.
• W3134815509 creator A5019256819 @default.
• W3134815509 creator A5030416562 @default.
• W3134815509 creator A5031000559 @default.
• W3134815509 creator A5074697107 @default.
• W3134815509 date "2021-06-01" @default.
• W3134815509 modified "2023-10-05" @default.
• W3134815509 title "A novel semi-supervised ensemble algorithm using a performance-based selection metric to non-stationary data streams" @default.
• W3134815509 cites W1518640223 @default.
• W3134815509 cites W1525647652 @default.
• W3134815509 cites W1904826605 @default.
• W3134815509 cites W1968817125 @default.
• W3134815509 cites W1990079212 @default.
• W3134815509 cites W2000454347 @default.
• W3134815509 cites W2000950277 @default.
• W3134815509 cites W2003917738 @default.
• W3134815509 cites W2009727399 @default.
• W3134815509 cites W2016159616 @default.
• W3134815509 cites W2021739900 @default.
• W3134815509 cites W2044574055 @default.
• W3134815509 cites W2045938006 @default.
• W3134815509 cites W2048679005 @default.
• W3134815509 cites W2052005199 @default.
• W3134815509 cites W2068462258 @default.
• W3134815509 cites W2099223662 @default.
• W3134815509 cites W2099419573 @default.
• W3134815509 cites W2119939946 @default.
• W3134815509 cites W2122951085 @default.
• W3134815509 cites W2124499489 @default.
• W3134815509 cites W2133088989 @default.
• W3134815509 cites W2133556223 @default.
• W3134815509 cites W2134125037 @default.
• W3134815509 cites W2136246134 @default.
• W3134815509 cites W2141245797 @default.
• W3134815509 cites W2143991132 @default.
• W3134815509 cites W2160512933 @default.
• W3134815509 cites W2165396616 @default.
• W3134815509 cites W2245547611 @default.
• W3134815509 cites W2317592095 @default.
• W3134815509 cites W2517990807 @default.
• W3134815509 cites W2555003309 @default.
• W3134815509 cites W2555947201 @default.
• W3134815509 cites W2585528949 @default.
• W3134815509 cites W2587928331 @default.
• W3134815509 cites W2600796512 @default.
• W3134815509 cites W2606013202 @default.
• W3134815509 cites W2626498001 @default.
• W3134815509 cites W2760845379 @default.
• W3134815509 cites W2767528836 @default.
• W3134815509 cites W2773675312 @default.
• W3134815509 cites W2795903893 @default.
• W3134815509 cites W2809841383 @default.
• W3134815509 cites W2911964244 @default.
• W3134815509 cites W2921074169 @default.
• W3134815509 cites W2945941367 @default.
• W3134815509 cites W2962805619 @default.
• W3134815509 cites W2977431930 @default.
• W3134815509 cites W3027401658 @default.
• W3134815509 cites W3105628676 @default.
• W3134815509 cites W64908097 @default.
• W3134815509 doi "https://doi.org/10.1016/j.neucom.2021.02.031" @default.
• W3134815509 hasPublicationYear "2021" @default.
• W3134815509 type Work @default.
• W3134815509 sameAs 3134815509 @default.
• W3134815509 citedByCount "10" @default.
• W3134815509 countsByYear W31348155092021 @default.
• W3134815509 countsByYear W31348155092022 @default.
• W3134815509 countsByYear W31348155092023 @default.
• W3134815509 crossrefType "journal-article" @default.
• W3134815509 hasAuthorship W3134815509A5019256819 @default.
• W3134815509 hasAuthorship W3134815509A5030416562 @default.
• W3134815509 hasAuthorship W3134815509A5031000559 @default.
• W3134815509 hasAuthorship W3134815509A5074697107 @default.
• W3134815509 hasConcept C11413529 @default.
• W3134815509 hasConcept C119857082 @default.
• W3134815509 hasConcept C124101348 @default.
• W3134815509 hasConcept C134306372 @default.
• W3134815509 hasConcept C136389625 @default.
• W3134815509 hasConcept C154945302 @default.
• W3134815509 hasConcept C162324750 @default.
• W3134815509 hasConcept C176217482 @default.
• W3134815509 hasConcept C187736073 @default.
• W3134815509 hasConcept C21547014 @default.
• W3134815509 hasConcept C2776135515 @default.
• W3134815509 hasConcept C2778484313 @default.
• W3134815509 hasConcept C2780898871 @default.
• W3134815509 hasConcept C33923547 @default.
• W3134815509 hasConcept C41008148 @default.
• W3134815509 hasConcept C42058472 @default.
• W3134815509 hasConcept C45942800 @default.
• W3134815509 hasConcept C50644808 @default.
• W3134815509 hasConcept C60777511 @default.
• W3134815509 hasConcept C76155785 @default.
• W3134815509 hasConcept C81917197 @default.
• W3134815509 hasConcept C89198739 @default.
• W3134815509 hasConceptScore W3134815509C11413529 @default.
• W3134815509 hasConceptScore W3134815509C119857082 @default.

• next