sample distribution
英 [ˈsɑːmpl ˌdɪstrɪˈbjuːʃn]
美 [ˈsæmpl ˌdɪstrɪˈbjuːʃn]
样品分布；样本分布；采样分布
英英释义
noun
- items selected at random from a population and used to test hypotheses about the population
双语例句
- About Sample Distribution of X2, T, F Statistic
关于X~2，T，F统计量的抽样分布 - The Digital Characters of the p norm sample Distribution
p-范分布母体抽样分布的数字特征 - The sample distribution of varied coefficient
变异系数的抽样分布 - This dissertation present another view, sample is an abstraction of the real world, and its space distribution conforms to regular rules, so the covering model can be seen as an approximation of the sample space distribution.
本文从另外一个角度考虑，认为样本是对客观世界的抽象描述，它在空间中的分布具有一定的规律，覆盖则是某种程度上对样本空间分布的一种近似。 - There were differences of range and percent between sample distribution and those of corresponding normal distribution for bust girth, waist girth, and hip girth.
胸围、腰围、臀围的分布范围和分布比例与正态分布存在差异。 - We use the information provided by sample projection distribution and sample size to determine the ratio of two classes of penalty factors and then obtain a new separating hyperplane.
该算法根据样本投影分布和样本容量所提供的信息给出两类惩罚因子比例，从而得到一个新的分离超平面。 - On the base of the situation in the sample distribution of feather space, it proposes object region extraction algorithm. Thirdly, achieve natural image object discernment system applying the Sparse Coding Theory.
在样本在特征空间分布情况分析基础上，提出对象区域提取算法。之后应用稀疏编码理论，实现自然图像对象识别系统。 - By balancing the training samples, dynamically resetting initial weights and adaptively evaluating net scales, some shortcomings of the BP algorithm, such as low convergence speed and high dependency on initial sample distribution are overcome, and the algorithm has become more robust and generic.
通过平衡训练样本数量、动态重置初始权值、评定网络规模等措施，解决了BP算法收敛速度慢、受初始样本分布影响大等缺陷，提高了识别算法的稳健性和泛化能力。 - Balanced and imbalanced data sets classification based on sample projection distribution
基于样本投影分布的平衡不平衡数据集分类 - This algorithm is applied on the computer cluster of the multi-node environment, using FCM to implement a algorithm to adjust the sample distribution, so that multiple classifiers can be trained simultaneously on multiple nodes.
该算法应用在多节点环境的计算机集群上，用FCM算法实现一种样本权重修正算法，使得多节点能够同时训练多个分类器。