在 中文 中使用 聚类 的示例及其翻译为 英语
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下图是其中一个作业的结果，词向量的t-SNE投影，通过相似性进行聚类。
Here is an outcome of one of the assignments, a t-SNE projection of word vectors, clustered by similarity.这些模型涉及识别，分类，聚类和信息检索，对于适应光伏系统检测方法非常有用。
These models involve recognition, classification, clustering, and information retrieval, and are useful for adapting PV system inspection methods.将这些基因型与先前公布的基因型进行聚类分析，结果显示大部分菌株（78株）属于先前描述的A1.
Cluster analysis comparing these genotypes with previously published genotypes indicated that most(n= 78) isolates belonged to the previously described A1.他们的数据集由近900万个蛋白质序列组成，这些蛋白质序列通过来自2,300多个细菌基因组的相似性聚类。
Their dataset consisted of nearly nine million protein sequences clustered by similarity from more than 2,300 bacterial genomes.你将学习可以在聚类模型中使用的数据类型，以及如何缩放和转换数据以为在聚类模型中使用做准备。
You will learn what data types can be used in clustering models, and how to scale and transform data in preparation for use in clustering models.回到原始的高维特征空间，将歌曲聚类到用户定义数量的群组中（k=10能够很好地实现可视化目的）。
Back in the original high-dimensional feature space, cluster the songs into a user-defined number of groups(k=10 works well for visualization purposes).你将学会如何决定你应该为你的模型选择多少聚类，以及如何在Alteryx中验证你的聚类。
使用一组（30个）高信息量的“通用”基因，他们将基因组进行了分层聚类，以定义物种。
Using a set of 30 informative"universal" genes, they hierarchically clustered the genomes to define species.你将学习和实践各种非监督学习的方法，包括：随机优化、聚类、特征选择和转换，以及信息论。
You will learn about and practice a variety of Unsupervised Learning approaches, including: randomized optimization, clustering, feature selection and transformation, and information theory.聚类分析显示，疲劳往往是一个集群的症状，包括疼痛，睡眠障碍，焦虑/抑郁(4)的一部分。
Cluster analysis has shown that fatigue is often part of a 拓扑数据分析-专注于复杂数据的形状，并识别聚类和数据里面存在的任何统计意义。
Topological Data Analysis- focusing on the shape of complex data and identifying clusters and any statistical significance that is present within that data.训练过程可以是监督或无监督学习、加强学习、聚类、决策树或不同的深度学习方式。
The training process can be supervised or unsupervised learning, reinforcement learning, clustering, decision trees or different methods of“deep learning.”.聚类分析已经广泛地用在许多应用中，包括模式识别，数据分析，图像处理，以及市场研究。
Cluster analysis has been widely used in numerous applications, including pattern recognition, data analysis, image processing, and market research.括号中的数字表示大小失衡系数：即最大与最小聚类大小的相对差异。
The numbers given in parentheses denote the size imbalance factor: i.e., the relative difference of the sizes of largest and smallest clusters.但这并不是Scikit-learn的全部功能，它同样可以用来做降维，聚类等等任何你所能想到的。
But this is not the full functionality of Scikit-learn, it can also be used to do dimensionality reduction, clustering, whatever you can think of.聚类样本：集群是人口的一个子群体，尽可能地，包含了整个人口的所有特征。
Cluster sample: A 我最喜欢的一种理解我的网络如何解读训练数据的方式是可视化聚类。
One of my favorite ways of understanding how my networks are interpreting my training data is by visualizing clusters.训练过程可以是监督学习或无监督学习，强化学习，聚类算法、决策树或是不同的深度学习方法。
The training process can be supervised or unsupervised learning, reinforcement learning, clustering, decision trees or different methods of“deep learning.”.聚类中心确定之后，剩余点被分配给与其具有较高密度的最近邻居相同的类簇。
After the cluster centers have been found, each remaining point is assigned to the same 你需要从数据中选择随机的k个点，并将它们命名为聚类的中心。
You need to select random k points from your data and name them centers of clusters.
