心理学专业词汇翻译辞典 - MBA智库文档 ... biased sample 偏性样本biased sampling偏性抽样biased statistic 有偏统计量 ... doc.mbalib.com|基于19个网页 2. 偏差抽样 4.偏差抽样(biased sampling)5. 共变评监(covariation assessment)—由一个变项预测另一个变项。
L. (1972). Size biased sampling. Technometrics, 14, 635-644.Scheaffer, R.L: Size biased sampling, Technometrics, 14(1972), 635-644.Scheaffer, R. (1972).Size biased sampling. Technometrics, 14, 635-644.Scheaffer, RL (1972) Size biased sampling. Technometrics 14: pp. 635-644...
- Added support for homogeneous and heterogeneous biased neighborhood sampling ([#247](https://github.com/pyg-team/pyg-lib/pull/247), [#251](https://github.com/pyg-team/pyg-lib/pull/251)) - Added dispatch for XPU device in `index_sort` ([#243](https://github.com/pyg-team/pyg-lib...
In particular, the function w(t)=t 卤 has important applications, including length-biased sampling (卤=1) and area-biased sampling (卤=2). We first consider here the maximum likelihood estimation of the parameters of a distribution f(t) under biased sampling from a censored population in a...
Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias‐free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still ...
2.1.3 Length-Biased Sampling Length-biased sampling is usually understood to refer to the special situation of random left truncation when the truncation variables are independently and uniformly distributed on some defined interval. When the truncating distribu- tion, G, is uniform, Wang called ...
必应词典为您提供biased-sampling-method的释义,网络释义: 偏性抽样法;混合样品法;
In this paper, we propose BiasedWalk, a scalable, unsupervised feature learning algorithm that is based on biased random walks to sample context information about each node in the network. Our random-walk based sampling can behave as Breath-First-Search (BFS) and Depth-First-Search (DFS) ...
Focusing on the latter, we propose to improve sampling-based attacks with prior beliefs about the target domain. We identify two such priors, image frequency and surrogate gradients, and discuss how to integrate them into a unified sampling procedure. We then formulate the Biased Boundary Attack,...