A Study of Applying Sub-Dimensional Approach to k-Means Clustering
碩士 === 臺南師範學院 === 教師在職進修資訊碩士學位班 === 92 === Clustering is one of the most popular methods in data mining. Clustering can rapidly and efficiently create high similar group and decrease the complexity in the same group to continue other technologies of data mining. So clustering is usually used as a pr...
Main Authors: | Shu-Mei Cheng, 鄭淑美 |
---|---|
Other Authors: | Chien-I Lee |
Format: | Others |
Language: | zh-TW |
Published: |
2004
|
Online Access: | http://ndltd.ncl.edu.tw/handle/02372725292064626427 |
Similar Items
-
A Study of Applying Sub-Dimensional Approach to k-Means Clustering
by: Shu-Mei Cheng, et al.
Published: (2004) -
Dimensionality reduction for k-means clustering
by: Musco, Cameron N. (Cameron Nicholas)
Published: (2016) -
Personality Classification Experiment by Applying k-Means Clustering
by: Assem Talasbek, et al.
Published: (2020-08-01) -
An Extended Regularized K-Means Clustering Approach for High-Dimensional Customer Segmentation With Correlated Variables
by: Hong-Hao Zhao, et al.
Published: (2021-01-01) -
Centroid Update Approach to K-Means Clustering
by: BORLEA, I.-D., et al.
Published: (2017-11-01)