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Cited by 304 publications
(87 citation statements)
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“…The application of MBO for these problems is another interesting research area. Finally, perturb [77], ensemble [78], learning mechanisms [79,80], or information feedback mechanisms [81] can be effectively combined with MBO to improve performance.…”
Section: Discussionmentioning
confidence: 99%
“…The application of MBO for these problems is another interesting research area. Finally, perturb [77], ensemble [78], learning mechanisms [79,80], or information feedback mechanisms [81] can be effectively combined with MBO to improve performance.…”
Section: Discussionmentioning
confidence: 99%
“…(1) The first technique considers the features that correspond to the monitoring sensors that are used for collecting the data from the monitoring sensors: six features (chest sensor), six features (right wrist sensor), six features (left ankle sensor), six features (right hip sensor); (2) The second technique considers the following three feature selection algorithms from literature: the forward feature selection (FFS) algorithm [38], the backward features elimination (BFE) algorithm [39] and the random forest (RF) [40]; (3) The third technique considers the BPSO algorithm adapted for data generated by monitoring sensors placed on the bodies of the monitored subjects; (4) The fourth technique considers adapted versions of genetic algorithm (GA) [41] and differential evolution (DE) [42] for feature selection using the same objective function as in the case of the adapted BPSO algorithm;…”
Section: Feature Selectionmentioning
confidence: 99%
“…Various methods have been developed for the task of feature selection in the unsupervised setting. Most of existing works distinguish these algorithms into three groups, i.e., filter [2], [4], [10], wrapper and embedded approaches [11]- [13], in terms of different selection strategy. Moreover, with the absent of supervised information, one of the key problem for unsupervised feature selection is to design the appropriate criterion to guide the search of relevant and informative features.…”
Section: Related Work a Unsupervised Feature Selectionmentioning
confidence: 99%