Prediction of Underlying Latent Classes via Alternate K-means Clustering Algorithms
碩士 === 國立交通大學 === 統計學研究所 === 98 === Parameters in latent class analysis could be estimated by some clustering methods. But in the high-dimensional data, variable selection in cluster analysis is an important problem. Here, we propose an alternate k-means clustering method to first distinguish cluste...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/00578490091908881611 |