Computing Association

Then , a new method for computing association probabilities using mean-field approximation network is presented .

在此基础上，提出了用均场逼近网络快速计算关联概率的新方法。

Computing association probabilities using mean-field approximation networks

用均场逼近网络计算关联概率

CompTIA , the Computing Technology Industry Association , recently did an opinion study .

美国计算机行业协会（CompTIA）最近进行了一项问卷调查。

Referring to the idea of Association Matrix in electrical network theory and combining character of Line-loss computing , the association matrix A , which is a key step to transfer Electrical Model to Math Model , is designed .

借鉴电网络理论中关联矩阵的概念，结合配网理论线损计算的特点，构造出关联矩阵A。这是将庞大而复杂的电气模型（网络接线图）转换成数学模型的关键。

Facing the distributed file system of Distributed computing platform , these association rule mining algorithms will fail .

在面对分布式计算平台的分布式文件系统时，这些算法就失效了。

On the other hand , Naive Bayes is weighted by computing the confidence of association rules .

另一方面，通过关联规则的置信度，给朴素贝叶斯加权。

In dealing with small dataset , because each computing cluster deployment task to take some time , more serious waste of computing resources , the association rules based on Hadoop parallel algorithm is not suitable for the calculation of small-scale dataset .

在处理小规模的数据集时，由于每次计算集群部署和退出任务要花掉一些时间，计算资源浪费比较严重，因此基于Hadoop的并行关联规则算法不太适合小规模数据集的计算。