K-means algorithm via preprocessing technique and singular value decomposition for high dimension datasets

• 主要作者: Usman, Dauda
• 格式: Thesis
• 語言: English
• 出版: 2014
• 主題: QA Mathematics
• 在線閱讀: http://eprints.utm.my/id/eprint/77643/1/DaudaUsmanPFS2014.pdf; http://eprints.utm.my/id/eprint/77643/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:98594

Data clustering is an unsupervised classification method aimed at creating groups of objects, or clusters that are distinct. Among the clustering techniques, Kmeans is the most widely used technique. Two issues are prominent in creating a Kmeans clustering algorithm; the optimal number of clusters a...