1) weights update
权系数更新
2) updating coefficients
系数更新
3) data update system
数据更新系统
4) 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。
5) 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。
6) renewal function
更新函数
1.
In order to accurately decide vehicle optimum maintenance period under availability objective,the renewal function of renewal theory and optimum concept was analyzed,two mathematical models of optimum maintenance period were established,and their optimum objectives were the greatest availability and the shortest total unworkable time in unit time respectively.
为准确确定有效性目标下的车辆最优维护周期,基于更新理论中的更新函数以及优化概念,分别建立了以有效度最大和以单位时间内总停驶时间最少为目标的2个最优维护周期数学模型。
2.
According to the need of engineering application and the prerequisite that the fault or life obeys Weibull distribution,the determining methods of renewal function under different conditions have been researched specially.
根据工程应用的需要,基于威布尔分布的前提条件,对不同情况下更新函数的确定方法进行专门研究。
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