Allegra J Midgette, Kelly Lynn Mulvey
White American Students' Recognition of Racial Microaggressions in Higher Education
Journal of diversity in higher education
todays datadriven digital culture critical demand optimized solutions essentially reduce operating expenses attempting increase productivity amount memory processing time used process enormous volumes data subject number limitations would undoubtedly problem dataset contained redundant uninteresting information instance many datasets contain number noninformative features primarily deceive given classification algorithm order tackle researchers developing variety feature selection fs techniques aim eliminate unnecessary information raw datasets putting front machine learning ml algorithm metaheuristic optimization algorithms often solid choice solve nphard problems like fs study present wrapper fs technique based sparrow search algorithm ssa type metaheuristic ssa swarm intelligence si method stands quick convergence improved stability ssa drawbacks like lower swarm diversity weak exploration ability late iterations like majority si algorithms using ten chaotic maps try ameliorate ssa three ways initial swarm generation ii substitution two random variables ssa iii clamping sparrows crossing search range result get cssa chaotic form ssa extensive comparisons show cssa superior terms swarm diversity convergence speed solving various representative functions institute electrical electronics engineers ieee congress evolutionary computation cec benchmark set furthermore experimental analysis cssa eighteen interdisciplinary multiscale ml datasets university california irvine uci data repository well three highdimensional microarray datasets demonstrates cssa outperforms twelve stateoftheart algorithms classification task based fs discipline finally 5significancelevel statistical posthoc analysis based wilcoxons signedrank test friedmans rank test nemenyis test confirms cssas significance terms overall fitness classification accuracy selected feature size computational time convergence trace stability