sample distribution

英 [ˈsɑːmpl ˌdɪstrɪˈbjuːʃn]

美 [ˈsæmpl ˌdɪstrɪˈbjuːʃn]

样品分布；样本分布；采样分布

计算机经济

英英释义

noun

• items selected at random from a population and used to test hypotheses about the population
  Synonym:samplesampling

双语例句

• Interval Estimates and Hypothetical Test Metod of Parameter On Few Sample Uniform Distribution
  小样本的均匀分布参数的区间估计和假设检验
• 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。
• 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。
• Flow fields and the sample particle distribution were calculated under different circumstances.
  计算了不同情况下的流场分布和样本粒子分布。
• About Sample Distribution of X2, T, F Statistic
  关于X~2，T，F统计量的抽样分布
• The Applying of Heteroscedastic Sample Sampling Distribution to the Test of the Guangxi White Pig Breeding
  异方差样本的抽样分布在广西白猪育种试验中的应用
• Linearized sample cumulative distribution frequency
  线性化样本累积分布频数
• 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 result shows that, due to the effect of the parameters 'priori distribution, there is essential difference between the sample predictive distribution and its original statistical distribution, the former being the matrix t distribution and the latter matrix normal distribution.
  研究结果表明：由于参数先验分布的作用，样本的预报分布与其原统计分布有着本质性的差异，前者为从矩阵正态分布，而后者为矩阵t分布。
• 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。