Select 3 as the maximum number of clusters and Kohonen as the clustering algorithm.
选择3作为集群的最大值并用Kohonen作为集群算法。
Run the clustering algorithm of choice using one of the many Hadoop-ready driver programs available in Mahout.
使用Mahout中可用的 Hadoop 就绪的驱动程序运行所选集群算法。
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.
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。
DBSCAN is a spatial clustering algorithm based on density.
DBSCAN是一个基于密度的聚类算法。
Meanwhile, the research of the stream data clustering algorithm would be useful references to the similar researches.
同时，本文对流数据聚类算法的研究，对于促进同类问题的研究具有一定的理论价值和借鉴意义。
This paper studies a combination clustering algorithm.
研究了一种聚类组合算法。
BIRCH algorithm is a clustering algorithm for very large datasets.
BIRCH算法是针对大规模数据集的聚类算法。
This paper introduced a density grid-based data stream clustering algorithm.
提出了一种基于密度网格的数据流聚类算法。
Based on the criterion a clustering algorithm named CACSS has been designed.
依据该评价方法，设计了面状地理实体聚类算法CACSS。
A new heuristic density-based ant colony clustering algorithm (HDACC) is presented.
提出一种基于密度的启发性群体智能聚类算法。
Fuzzy c-clustering algorithm (FCM) is a useful tool in edge detection of digital image.
模糊聚类算法(FCM)应用于数字图像的边缘检测已取得了较好的效果。
A fast clustering algorithm with adaptive density based on homogeneous grid is proposed.
提出了一种基于均匀网格的自适应密度快速聚类新算法。
The paper presents an ant colony clustering algorithm based on directional similarity: ACCADS.
提出了一种基于方向相似性度量的蚁群聚类算法。
A fault alarms correlation rule analysis model based on sequence clustering algorithm is designed.
设计了基于序列聚类算法的故障告警关联规则分析模型。
This paper proposes a rough spectral clustering algorithm and apply the algorithm on text data mining.
该文提出了一种粗糙谱聚类算法，并将其应用于文本数据挖掘。
A clustering algorithm for Chinese documents based on the spherical fuzzy c-means algorithm is presented.
提出一种基于球形的模糊c -均值算法的中文文本聚类方法。
Proposed dynamic clustering algorithm has strong robustness in clustering of time series multi-dimensional data.
本文算法对于时序数据的聚类具有较强的鲁棒性。
This paper proposes a modified fuzzy C-means (MFCM) clustering algorithm to cluster all images before retrieval.
论文采用了一种基于改进的模糊C均值算法来聚类图像。
An improved color segmentation algorithm is presented based on weighting fuzzy c-means (FCM) clustering algorithm.
在加权模糊c -均值(FCM)聚类算法的基础上，对分色算法进行了改进。
Based on clone selection theory and typical partition clustering approach, a new clustering algorithm is proposed.
将克隆选择原理同典型的划分聚类方法结合起来，提出一种克隆选择聚类算法。
It is hard to cluster high-dimensional data using traditional clustering algorithm because of the sparsity of data.
在高维空间中，由于数据的稀疏性，传统的聚类方法难以有效地聚类高维数据。
Realize the clustering algorithm part of the recommendation system based on collaborative filtering and evaluate it.
对基于聚类的协同过滤推荐系统的聚类算法进行了实现和评价。
Next, based on the analysis of deficiency of BIRCH algorithm, we propose a new clustering algorithm based on sampling.
随后，在分析BIRCH算法不足的基础上，提出了一种基于抽样的聚类算法。
The cluster distance computing method is the key issue affecting the performance of hierarchical clustering algorithm.
在聚类的过程中簇间距离计算的准确性是影响算法性能的重要因素。
Aimed at the automatic color segmentation of topographic maps, a new effective fuzzy clustering algorithm is presented.
针对彩色地形图的自动分色问题，提出了一种新的模糊聚类算法。
Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.
结果模糊K- 均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、 白质和脑脊液。
The new clustering algorithm is analyzed on several aspects and tested on the published yeast cell-cycle microarray data.
从多方面分析了该算法的性能，并将该算法应用于酵母细胞周期的芯片表达谱数据聚类。
By analyzing ART2 neural network clustering algorithm, an improved ART2 neural network clustering algorithm was proposed.
分析了现有ART2网络存在的问题，提出了一种改进的ART2算法。
A novel clustering algorithm based on Bayesian model was introduced into the analysis of large-scale gene expression profiles.
在大规模基因表达谱的数据分析中引入了一种全新的基于贝叶斯模型的聚类算法。
A novel clustering algorithm based on Bayesian model was introduced into the analysis of large-scale gene expression profiles.
在大规模基因表达谱的数据分析中引入了一种全新的基于贝叶斯模型的聚类算法。
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