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- 聚类问题K-Means算法K-Means algorithm
- 蚁群算法及其在Flow Shop问题和聚类问题上的应用ACA and Its Application on Flow Shop Problem and Clustering Problem
- 一类半线性椭圆边值问题k-波节解的唯一性THE UNIQUENESS OF K-NODE SOLUTIONS FOR SOME SEMILINEAR ELLIPTIC PROBLEMS
- 聚类问题clustering problem
- 聚类分析cluster analysis
- 模糊K原型聚类算法Fuzzy K-Prototypes clustering algorithm
- 自组织竞争人工神经网络在聚类问题中的运用Application of Self-organizing NNs in Cluster
- 聚类算法clustering algorithm
- K中心点聚类K-medoids clustering algorithm
- 快速K均值聚类quick K-means cluster
- ATR聚类算法clustering algorithm
- K-均值聚类法K - means clustering
- 相似性的度量是解决聚类问题的关键,而分类属性的相似性无法用欧几里德(Euclidean)距离来度量.Similarity measurement is the key to solving the clustering problem, while similarity of categorical attributes can'be measured by Euclidean distance.
- FCM聚类算法FCM Clustering Algorithm
- k均值聚类法则K-means Cluster method
- 核聚类算法kernel clustering algorithm
- K均值聚类分析K-means clustering
- 灰色聚类的几个问题Some Questions on Grey Clustering
- 减聚类算法subtractive clustering algorithm
- 模糊K-原型聚类fuzzy K-prototypes clustering
