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

• Linearized sample cumulative distribution frequency
  线性化样本累积分布频数
• At the same time, the representative pre-miRNAs are selected according to the pre-miRNA sample distribution as training samples.
  同时，基于miRNA前体在样本空间中分布，选择有代表性的miRNA前体作为训练样本。
• 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。
• 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
• 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 work of estimating the tail dependence coefficient is simple, when the sample distribution is known and the observation data is enough, the banks can use the parametric model to estimate the coefficient. But in real world, these conditions always can not satisfy.
  尾部相关系数的估算较为便利，当样本分布已知且样本数据量充足时，采用参数估计尾部相关系数是非常有效的。但在信用风险管理中，这些条件有时并不具备。
• 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。
• In this paper, suppose that the sample distribution of AR ( p) sequence is an elliptical distribution, or the white noise of AR ( p) sequence is elliptical white noise.
  本文中，设AR（p）序列的样本分布为椭球分布，AR（p）序列的噪声为椭球白噪声。
• About Sample Distribution of X2, T, F Statistic
  关于X~2，T，F统计量的抽样分布
• 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。