至此，我们已经可以运行这个群集算法了。
At this point, we are ready to run the clustering algorithm.
群集算法是对一个数据集中的数据进行分组，以便您可以基于在这些组中看到的趋势得出结论。
The clustering algorithm takes a data set and sorts them into groups, so you can make conclusions based on what trends you see within these groups.
最后，我们想要通过单击SimpleKMeans调整我们群集算法的属性(虽然不是最佳的UI设计，但还是先接受吧)。
Finally, we want to adjust the attributes of our cluster algorithm by clicking SimpleKMeans (not the best UI design here, but go with it).
本文讨论了两种数据挖掘算法：分类树和群集。
This article discussed two data mining algorithms: the classification tree and clustering.
如下是对群集中所用算法的一个简要的快速概览。
This should be considered a quick and non-detailed overview of the math and algorithm used in the clustering method.
这里我们想要调整的这个算法的惟一属性是numClusters字段，它表明我们想要创建多少群集。
The only attribute of the algorithm we are interested in adjusting here is the numClusters field, which tells us how many clusters we want to create.
本文讨论了群集智能的两种算法，蚁群智能与微粒群智能。
In this paper, we review ant colony algorithm and particle swarm optimization.
粒子群算法是基于群集智能、受到人工生命研究结果的启发而提出的一种现代优化方法。
Based on the swarm intelligence, Particle swarm optimization (PSO) algorithm is a kind of modern optimization method inspired by the research of the artificial life.
微粒群优化算法（PSO）是目前备受关注的群集智能算法的代表性方法，也是本文研究工作的算法基础。
As a representative swarm-intelligence based optimization algorithm, Particle SwarmOptimization (PSO) algorithm is applied to capacitor optimization in the dissertation.
提出了一种求解群集机器人协作任务规划问题的均分点蚁群算法(EDPACA)。
An equal division point ant colony algorithm (EDPACA) was proposed to solve the swarm-robot mission planning problem.
基于群集智能的优化算法是一种仿生自然界动物昆虫觅食、筑巢行为的模拟进化算法。
Optimization algorithm based on the swarm intelligence is a simulated evolutionary method that simulating the behaviors of social insects searching for food and building of nest.
研究高效的群集通信算法对并行计算效率的提升有着重要的作用。
Efficient collective communications algorithm plays a vital role in improving the performance of parallel computation.
研究高效的群集通信算法对并行计算效率的提升有着重要的作用。
Efficient collective communications algorithm plays a vital role in improving the performance of parallel computation.
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