Matches in SemOpenAlex for { <https://semopenalex.org/work/W3048981013> ?p ?o ?g. }
- W3048981013 endingPage "218" @default.
- W3048981013 startingPage "205" @default.
- W3048981013 abstract "Feature selection is a complex optimization problem with important real-world applications. Normally, its main target is to reduce the dimensionality of the dataset and increase the effectiveness of the classification. Owing to the population-inspired characteristics, different evolutionary algorithms (EAs) have been proposed to solve feature selection problems over the past decades. However, the majority of them only consider single-objective optimization while many real-world problems have multiple objectives, which creates a genuine demand for designing more suitable and effective EAs to handle multiobjective feature selection. A multiobjective feature selection problem usually consists of two objectives: one is to minimize the number of selected features and the other is to minimize the error of classification. In this article, we propose a duplication analysis-based EA (DAEA) for biobjective feature selection in classification. In the proposed algorithm, we make improvements on the basic dominance-based EA framework in three aspects: first, the reproduction process is modified to improve the quality of offspring; second, a duplication analysis method is proposed to filter out the redundant solutions; and third, a diversity-based selection method is adopted to further select the reserved solutions. In the experiments, we have compared the proposed algorithm with five state-of-the-art multiobjective EAs (MOEAs) and tested them on 20 classification datasets, using two widely used performance metrics. According to the empirical results, DAEA performs the best on most datasets, indicating that DAEA not only gains outstanding optimization performance but also obtains good classification and generalization results." @default.
- W3048981013 created "2020-08-21" @default.
- W3048981013 creator A5016371456 @default.
- W3048981013 creator A5062501830 @default.
- W3048981013 creator A5077569089 @default.
- W3048981013 date "2021-04-01" @default.
- W3048981013 modified "2023-10-15" @default.
- W3048981013 title "A Duplication Analysis-Based Evolutionary Algorithm for Biobjective Feature Selection" @default.
- W3048981013 cites W1158789509 @default.
- W3048981013 cites W1418108976 @default.
- W3048981013 cites W1543715688 @default.
- W3048981013 cites W1575601714 @default.
- W3048981013 cites W1588375755 @default.
- W3048981013 cites W1608317386 @default.
- W3048981013 cites W1659842140 @default.
- W3048981013 cites W1662894842 @default.
- W3048981013 cites W1922991060 @default.
- W3048981013 cites W1964042173 @default.
- W3048981013 cites W1967230147 @default.
- W3048981013 cites W1968219458 @default.
- W3048981013 cites W1987958230 @default.
- W3048981013 cites W1989268897 @default.
- W3048981013 cites W2005292390 @default.
- W3048981013 cites W2011048370 @default.
- W3048981013 cites W2013885787 @default.
- W3048981013 cites W2017337590 @default.
- W3048981013 cites W2020320008 @default.
- W3048981013 cites W2022485595 @default.
- W3048981013 cites W2023658415 @default.
- W3048981013 cites W2023685757 @default.
- W3048981013 cites W2025822274 @default.
- W3048981013 cites W2032101114 @default.
- W3048981013 cites W2038420231 @default.
- W3048981013 cites W2039667767 @default.
- W3048981013 cites W2047094503 @default.
- W3048981013 cites W2050399271 @default.
- W3048981013 cites W2055142708 @default.
- W3048981013 cites W2058142975 @default.
- W3048981013 cites W2063375245 @default.
- W3048981013 cites W2067544246 @default.
- W3048981013 cites W2072661909 @default.
- W3048981013 cites W2075016777 @default.
- W3048981013 cites W2085507535 @default.
- W3048981013 cites W2090096246 @default.
- W3048981013 cites W2090797242 @default.
- W3048981013 cites W2095213774 @default.
- W3048981013 cites W2095987703 @default.
- W3048981013 cites W2098116891 @default.
- W3048981013 cites W2098907614 @default.
- W3048981013 cites W2102365077 @default.
- W3048981013 cites W2102625537 @default.
- W3048981013 cites W2102831150 @default.
- W3048981013 cites W2108968575 @default.
- W3048981013 cites W2109928590 @default.
- W3048981013 cites W2116661285 @default.
- W3048981013 cites W2118561568 @default.
- W3048981013 cites W2120091775 @default.
- W3048981013 cites W2124258777 @default.
- W3048981013 cites W2126105956 @default.
- W3048981013 cites W2133462743 @default.
- W3048981013 cites W2135974394 @default.
- W3048981013 cites W2142331156 @default.
- W3048981013 cites W2143381319 @default.
- W3048981013 cites W2147573707 @default.
- W3048981013 cites W2150046657 @default.
- W3048981013 cites W2153654820 @default.
- W3048981013 cites W2283268937 @default.
- W3048981013 cites W2316628860 @default.
- W3048981013 cites W2326149522 @default.
- W3048981013 cites W2329749247 @default.
- W3048981013 cites W2336467679 @default.
- W3048981013 cites W2343420905 @default.
- W3048981013 cites W2343601797 @default.
- W3048981013 cites W2344916885 @default.
- W3048981013 cites W2398981591 @default.
- W3048981013 cites W2414607481 @default.
- W3048981013 cites W2477870999 @default.
- W3048981013 cites W2510493362 @default.
- W3048981013 cites W2588272390 @default.
- W3048981013 cites W2596496399 @default.
- W3048981013 cites W2745573163 @default.
- W3048981013 cites W2764251381 @default.
- W3048981013 cites W2780725426 @default.
- W3048981013 cites W2785722638 @default.
- W3048981013 cites W2800879376 @default.
- W3048981013 cites W2888338796 @default.
- W3048981013 cites W2897301007 @default.
- W3048981013 cites W2939164430 @default.
- W3048981013 cites W2943480356 @default.
- W3048981013 cites W2946739419 @default.
- W3048981013 cites W2953877793 @default.
- W3048981013 cites W2968688008 @default.
- W3048981013 cites W3004476750 @default.
- W3048981013 cites W4212817109 @default.
- W3048981013 cites W4256661862 @default.
- W3048981013 doi "https://doi.org/10.1109/tevc.2020.3016049" @default.
- W3048981013 hasPublicationYear "2021" @default.
- W3048981013 type Work @default.