1) weight updating scheme
权值更新
1.
In this paper,a featureselection algorithm based on weight updating scheme of Adaboost and K-L distance is proposed.
本文提出一种基于Adaboost权值更新以及K-L距离的特征选择算法,在Adaboost的每一轮训练中动态地选择所有备选边界片段的一个子集作为Adaboost训练的特征集。
2) weight updating
权重更新
1.
Through comparing the weight updating in the traditional Adaboost algorithm,this paper presents a new algorithm of updating the weight,which combines the normalization process of the same type and between the different types.
通过比较传统的Adaboost算法中样本权重的更新算法,提出了一种新的将类内归一化与全局归一化过程相结合的样本权重更新算法。
2.
The effects of different weight updating approaches of Adaboost on the performance of classifiers are analyzed respectively.
从样本集归一化和样本权重更新两个角度分析了各种权重更新方法对分类器性能的影响，提出了一种扩展的样本权重更新方法，在保证样本整体错分率的情况下，能降低正样本的错分率。
3) Update of PCRs Value
PCR值更新
4) weights update
权系数更新
5) value-update rules
值更新规则
1.
For obtaining a satisfactory shortest path, this paper proposed an improved LRTA~* to speed up search algorithm convergence through changing value-update rules.
为获得满意解为目标的最优路径选择问题,给出了一种加权的LRTA (LearningReal TimeA )算法,通过改变估价函数值更新规则与解时间和解质量的相对折中,加快算法收敛速度。
2.
In this paper,a new method to speed up its convergence through changing value-update rules is proposed.
本文给出了通过改变值更新规则来加快实时算法收敛的一种新方法,通过时间和解质量的相对折中,使该算法比LRTA*算法更快地收敛于满意解,是一种求解大城市稠密路网两点间最优路径的有效方法。
6) new weight
新权值
1.
With the methods of statistics,472 men and 299 women undergraduates at our college were regarded as samples,the normal;variance and mean of Constitution and Health scores were discussed based on 16 sets of weights in order to extract the new weight,viz.
用数理统计法讨论了我院472名男生和299名女生在16组权值下体质健康成绩的正态性、方差和均值,以抽取新权值(20:15:30:15:20)。
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参考词条