Time space tradeoffs in GA based feature selection for workload characterization
作者： Dan E. Tamir , Clara Novoa , Daniel Lowell
DOI: 10.1007/978-3-642-13025-0_66
关键词:
摘要: This paper reports the results of a research effort that explores time/space tradeoffs inherent to genetic algorithms (GA). The study analyzes redundancy in GA search space and lays out schema for efficient utilization record keeping form cache minimize redundancy. application used evaluation procedure is feature selection computer workload characterization. experimental demonstrate utility domain, show significant reduction execution time with virtually same solution quality.
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