非参数统计
选择(遗传算法)
集合(抽象数据类型)
数学
班级(哲学)
样品(材料)
测量不确定度
算法
计算机科学
统计
人工智能
色谱法
化学
程序设计语言
标识
DOI:10.1109/t-c.1971.223410
摘要
A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements. The measurement subset evaluation procedure directly employs a nonparametric estimate of the probability of error given a finite design sample set. A suboptimum measurement subset search procedure is employed to reduce the number of subsets to be evaluated. Teh primary advantage of the approach is the direct but nonparametric evaluation of measurement subsets, for the M class problem.
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